网易山东烟台网友[wcskqlm](218.56.*.*) 的原贴： 1
布吕尼一回头.............
网易辽宁大连网友 [白旗] 的原贴： 2
山崩地裂水倒流..........
网易福建福州网友[jxh680](120.32.*.*) 的原贴： 3
布吕尼二回头····
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萨科齐头上绿油油
网易北京朝阳网友[s13](221.221.*.*) 的原贴： 5
布吕尼三回头····
网易广东深圳网友[老萨](58.250.*.*) 的原贴： 6
万户萧疏鬼见愁
网易山东青岛网友[11](60.209.*.*) 的原贴： 7
布吕 尼四回头......
网易河北邢台网友 [lovecctv] 的原贴： 8
老虎上树猪跳楼
网易浙江杭州网友[windows3000](122.235.*.*) 的原贴： 9
布吕 尼五回头......
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一枝红杏出墙头
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布吕尼 六回头
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一股春水往下流
网易广东惠州网友[专业盖楼](116.17.*.*) 的原贴： 13
布吕尼 七回头
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哈雷彗星撞地球
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布吕尼 八回头
网易荷兰网友[发烂稀](213.197.*.*) 的原贴： 16
粪土高卢万户侯
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布吕尼 九回头
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长江之水倒着流
网易辽宁辽阳网友[AA](60.19.*.*) 的原贴： 19
布吕尼 十回头
网易福建厦门网友 [k7995443] 的原贴： 20
小裤裤罩不住铁枪头
网易福建福州网友 [buyi-03] 的原贴： 21
笑死老夫了!
网易江苏盐城网友[123](61.177.*.*) 的原贴： 22
布吕尼 十一回头
网易浙江杭州网友[zhouxuyao888](125.122.*.*) 的原贴： 23
万里长城抖三抖
网易浙江杭州网友[zhouxuyao888](125.122.*.*) 的原贴： 24
布吕尼 十二回头
网易山东滨州网友 [bingzhouren] 的原贴： 25
萨科奇的JJ不顶用
网易中国网友[wangyi163pinglun](119.45.*.*) 的原贴： 26
布吕尼 十三回头
网易北京丰台网友 [sinfiasong] 的原贴： 27
布吕尼掉了头
网易广东汕头网友[调查](116.26.*.*) 的原贴： 28
布吕尼 十四回头
网易福建厦门网友 [k7995443] 的原贴： 29
无数蝌蚪墙上游
网易广东深圳福田网友[huai1102](218.18.*.*) 的原贴： 30
布吕尼脱了再回头
网易江苏网友[534](114.218.*.*) 的原贴： 31
乔丹改打乒乓球
网易广东佛山网友[sb](121.9.*.*) 的原贴： 32
布吕尼 十六回头
网易四川成都网友[dfd](202.115.*.*) 的原贴： 33
范跑跑都要当诸侯
网易贵州毕节网友 [mpy1976] 的原贴： 34
布吕尼 十七回头
网易浙江丽水网友 [lly22] 的原贴： 35
太监都要翘翘头
网易浙江丽水网友 [lly22] 的原贴： 36
布吕尼 十八回头
网易北京门头沟网友[4234](222.129.*.*) 的原贴： 37
美女瞬间变骷髅
网易四川乐山网友 [em_xhr] 的原贴： 38
布吕尼 十九回头
网易福建福州网友 [163xzxz] 的原贴： 39
萨科齐挥泪斩归头
网易辽宁大连网友 [tommyxushuli] 的原贴： 40
布吕尼 二十回头
网易四川成都网友[110](222.209.*.*) 的原贴： 41
日晚挥刀来自宫
网易北京网友(124.193.*.*) 的原贴： 42
布吕尼 二十一回头
网易浙江宁波网友[huzhen102](220.189.*.*) 的原贴： 43
天上的星星参北斗...
网易四川成都网友[SPEAR](218.88.*.*) 的原贴： 44
布吕尼 二十二回头
网易山东济南网友[11](60.216.*.*) 的原贴： 45
和尚洗头用飘柔
网易广东揭阳网友[拽着红杏出墙](125.91.*.*) 的原贴： 46
布吕尼 二十三回头
网易广东广州网友[benny43](121.33.*.*) 的原贴： 47
蚊子学会狮子吼
网易吉林网友 [ioyou0707] 的原贴： 48
布吕尼 二十四回头
网易黑龙江佳木斯网友[鹅鹅鹅](222.172.*.*) 的原贴： 49
老萨枪头流出脓
2009年6月25日星期四
话题：朝鲜威胁让美国从地球上消失 美国防部称愚蠢
网易四川广安网友 [lei6232621]： 2009-06-25 18:37:25 发表
网易广东广州番禺网友[YY强过](218.19.*.*) 的原贴： 1
我是这样想的——挖个大通道，把太平洋的水引流进去，淹掉美国！！！
网易广东广州网友[↑](61.140.*.*) 的原贴： 2
楼上太不现实了，我是这样想的——用抽气机把美国的空气抽过来，让它窒息而亡！！！
网易新疆乌鲁木齐网友[!](222.60.*.*) 的原贴： 3
我是这样想的——把太阳挡住，不管地球怎么转都不让美国晒伤太阳。冻死他！
网易广东深圳福田网友 [有爹才好长] 的原贴： 4
我是这样想的，我让中*国大哥灭了你们。
网易江苏南京网友[njgexin](58.217.*.*) 的原贴： 5
我是这样想的——把所有天下下的雨全下到美国去，淹死它！！！
网易北京网友 [loftguy] 的原贴： 6
我是这样想的--派1000个带艾滋的美女特工，在5年内彻底清除美国人
网易广东深圳网友[222222](116.7.*.*) 的原贴： 7
我是这样想的，把全球的石油送到美国，点燃石油烧死美国佬
网易江西九江网友[wzhrm819](218.87.*.*) 的原贴： 8
我是这样想的,大家反复去美国公费旅游，回来时带把土，让美国变成海。
网易贵州遵义网友[lzchang8768](222.87.*.*) 的原贴： 9
这个方案很有创意，而且也可能是很现实而有效的办法！支持！
网易辽宁大连网友[eeee](60.20.*.*) 的原贴： 10
我是ye这样想的,大家反复去美国公费旅游，每个人干一个美国女人，让美国人后代变成华人。
网易浙江温州网友[jytdb](218.73.*.*) 的原贴： 11
讨论一下万一老美给灭了，世界该谁坐庄！
网易广东深圳宝安网友[蒙娜丽沙](219.133.*.*) 的原贴： 12
那还用说。当然是我中老大哟！
网易湖南长沙网友[15181](222.240.*.*) 的原贴： 13
中国去死吧
网易河南郑州网友 [skytrooper11] 的原贴： 14
我是这样想的，咱们都冲着地球那边打喷嚏，给丫搞细菌战，病死他们
网易湖北武汉网友[dfzz](59.175.*.*) 的原贴： 15
我是这样想的，派中国2000只精英城管，战无不胜。
网易浙江杭州网友 [gaochen19861] 的原贴： 16
2000城管会不会太多噢
网易浙江金华网友[wyplzyh](218.0.*.*) 的原贴： 17
15楼太残忍了
网易山东临沂网友[wuqinb](221.2.*.*) 的原贴： 18
15楼不按套路出牌啊
网易四川达州网友 [huang_089] 的原贴： 19
希望城管对美籍华人下手轻点就行了，
网易河南郑州网友[chuanshuozhikui(125.40.*.*) 的原贴： 20
15楼简直不是人！
网易天津网友[zhaochangqian](218.67.*.*) 的原贴： 21
2000个城管够毁灭美国十几次了，相当残忍！
网易广东东莞网友[ccg2000510](119.127.*.*) 的原贴： 22
毁灭的时候请文明执法，不要外伤，不要给记者拍到
网易北京网友 [lrhaf] 的原贴： 23
对让他们全部是被自杀的。
网易浙江嘉兴网友 [nimabwy163] 的原贴： 24
你们那些都不现实，真的，要我说派一个县的公务员过去，1年后美国经济完了那不就不牛B了吗，这叫兵不血刃。
网易四川眉山网友[1](218.89.*.*) 的原贴： 25
我是这样想的，让中国男足全部加入美国籍，天天让美国人看这群人踢球，恶心死他们
网易广西河池网友[1](202.103.*.*) 的原贴： 26
路过
网易福建泉州网友 [kvgnt] 的原贴： 27
我是来顶24楼的
网易辽宁大连网友 [黄金の太阳] 的原贴： 28
我 KAO!!!这个更 牛!!!!!牛人年年有,今年特别多!!!!
以上全是 天才!!! 老子佩服 的 五体投地!!!!
网易北京朝阳网友 [reiljuin8892] 的原贴： 29
综上所述，让城关去米国当公务员即可……
网易北京网友[123](124.193.*.*) 的原贴： 30
15楼简直不是人类，这么残忍的事也能想出来，美国再可恨也没可恨到那个程度吧？
网易浙江丽水网友[111](60.184.*.*) 的原贴： 31
哈怕
网易广东深圳宝安网友[0755](219.133.*.*) 的原贴： 32
15楼让我吃不下饭.你可要负有不可推卸的责任哦!
网易辽宁铁岭网友[雷死他们](123.244.*.*) 的原贴： 33
我是这样想滴__派录 军过去大说一通雷 死美 国人...~
:))
网易北京网友[beijintea](219.142.*.*) 的原贴： 34
我支持8楼
我支持8楼
我支持8楼
网易安徽网友[小李0947](117.70.*.*) 的原贴： 35
15楼你那样弄的不好会毁灭地球的
网易广东深圳网友[杨成勇](121.15.*.*) 的原贴： 36
我支持35楼的这位兄弟，天天给美国人讲笑话，让他们一个个笑死
网易上海徐汇网友[123](116.232.*.*) 的原贴： 37
我是这样想的：叫他们来买中国股票，让他们亏死
网易广东广州番禺网友[YY强过](218.19.*.*) 的原贴： 1
我是这样想的——挖个大通道，把太平洋的水引流进去，淹掉美国！！！
网易广东广州网友[↑](61.140.*.*) 的原贴： 2
楼上太不现实了，我是这样想的——用抽气机把美国的空气抽过来，让它窒息而亡！！！
网易新疆乌鲁木齐网友[!](222.60.*.*) 的原贴： 3
我是这样想的——把太阳挡住，不管地球怎么转都不让美国晒伤太阳。冻死他！
网易广东深圳福田网友 [有爹才好长] 的原贴： 4
我是这样想的，我让中*国大哥灭了你们。
网易江苏南京网友[njgexin](58.217.*.*) 的原贴： 5
我是这样想的——把所有天下下的雨全下到美国去，淹死它！！！
网易北京网友 [loftguy] 的原贴： 6
我是这样想的--派1000个带艾滋的美女特工，在5年内彻底清除美国人
网易广东深圳网友[222222](116.7.*.*) 的原贴： 7
我是这样想的，把全球的石油送到美国，点燃石油烧死美国佬
网易江西九江网友[wzhrm819](218.87.*.*) 的原贴： 8
我是这样想的,大家反复去美国公费旅游，回来时带把土，让美国变成海。
网易贵州遵义网友[lzchang8768](222.87.*.*) 的原贴： 9
这个方案很有创意，而且也可能是很现实而有效的办法！支持！
网易辽宁大连网友[eeee](60.20.*.*) 的原贴： 10
我是ye这样想的,大家反复去美国公费旅游，每个人干一个美国女人，让美国人后代变成华人。
网易浙江温州网友[jytdb](218.73.*.*) 的原贴： 11
讨论一下万一老美给灭了，世界该谁坐庄！
网易广东深圳宝安网友[蒙娜丽沙](219.133.*.*) 的原贴： 12
那还用说。当然是我中老大哟！
网易湖南长沙网友[15181](222.240.*.*) 的原贴： 13
中国去死吧
网易河南郑州网友 [skytrooper11] 的原贴： 14
我是这样想的，咱们都冲着地球那边打喷嚏，给丫搞细菌战，病死他们
网易湖北武汉网友[dfzz](59.175.*.*) 的原贴： 15
我是这样想的，派中国2000只精英城管，战无不胜。
网易浙江杭州网友 [gaochen19861] 的原贴： 16
2000城管会不会太多噢
网易浙江金华网友[wyplzyh](218.0.*.*) 的原贴： 17
15楼太残忍了
网易山东临沂网友[wuqinb](221.2.*.*) 的原贴： 18
15楼不按套路出牌啊
网易四川达州网友 [huang_089] 的原贴： 19
希望城管对美籍华人下手轻点就行了，
网易河南郑州网友[chuanshuozhikui(125.40.*.*) 的原贴： 20
15楼简直不是人！
网易天津网友[zhaochangqian](218.67.*.*) 的原贴： 21
2000个城管够毁灭美国十几次了，相当残忍！
网易广东东莞网友[ccg2000510](119.127.*.*) 的原贴： 22
毁灭的时候请文明执法，不要外伤，不要给记者拍到
网易北京网友 [lrhaf] 的原贴： 23
对让他们全部是被自杀的。
网易浙江嘉兴网友 [nimabwy163] 的原贴： 24
你们那些都不现实，真的，要我说派一个县的公务员过去，1年后美国经济完了那不就不牛B了吗，这叫兵不血刃。
网易四川眉山网友[1](218.89.*.*) 的原贴： 25
我是这样想的，让中国男足全部加入美国籍，天天让美国人看这群人踢球，恶心死他们
网易广西河池网友[1](202.103.*.*) 的原贴： 26
路过
网易福建泉州网友 [kvgnt] 的原贴： 27
我是来顶24楼的
网易辽宁大连网友 [黄金の太阳] 的原贴： 28
我 KAO!!!这个更 牛!!!!!牛人年年有,今年特别多!!!!
以上全是 天才!!! 老子佩服 的 五体投地!!!!
网易北京朝阳网友 [reiljuin8892] 的原贴： 29
综上所述，让城关去米国当公务员即可……
网易北京网友[123](124.193.*.*) 的原贴： 30
15楼简直不是人类，这么残忍的事也能想出来，美国再可恨也没可恨到那个程度吧？
网易浙江丽水网友[111](60.184.*.*) 的原贴： 31
哈怕
网易广东深圳宝安网友[0755](219.133.*.*) 的原贴： 32
15楼让我吃不下饭.你可要负有不可推卸的责任哦!
网易辽宁铁岭网友[雷死他们](123.244.*.*) 的原贴： 33
我是这样想滴__派录 军过去大说一通雷 死美 国人...~
:))
网易北京网友[beijintea](219.142.*.*) 的原贴： 34
我支持8楼
我支持8楼
我支持8楼
网易安徽网友[小李0947](117.70.*.*) 的原贴： 35
15楼你那样弄的不好会毁灭地球的
网易广东深圳网友[杨成勇](121.15.*.*) 的原贴： 36
我支持35楼的这位兄弟，天天给美国人讲笑话，让他们一个个笑死
网易上海徐汇网友[123](116.232.*.*) 的原贴： 37
我是这样想的：叫他们来买中国股票，让他们亏死
2009年6月11日星期四
List of References on Agent Based Land Use Simulations
As part of the 2004 RELU project on rural land use in the UK, we are reviewing agent-based simulations of land use. We are particularly interested in models which integrate social and ecological factors. We are trying to collect all the publications on this topic and have so far compiled the list below of 41 references.
If you know of any relevant models we have not included please could you email the details to us at ablum@hotmail.co.uk. We will update the list and hopefully leave a useful resource for anyone interested in this topic.
Many thanks for your help,
Dr Robin Matthews and Alan Roach
Agent Based Land Use Models Reference List
Axtell R et al (1999). Understanding Anasazi Culture Change Through Agent-Based Modelling. Dynamics in Human Primate Societies. T. Kohler and G. Gumerman.
Balmann, A., K. Happe, et al. (2003). Adjustment costs of agri-environmental policy switching: an agent-based analysis of the German region Hohenlohe. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Barreteau, O. and F. Bousquet (2000). "SHADOC; a multi-agent model to tackle viability of irrigated systems,." Annals of operations research.
Becu, N., P. Perez, et al. (2003). "Agent based simulation of a small catchment water management in northern Thailand: description of the CATCHSCAPE model." Ecological Modelling.
Berger, T. (2001). "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis." Agricultural economics.
Bousquet, F. and C. Page ( 2004). "Multi-agent simulations and ecosystem management: a review,." Ecological Modelling.
Bousquet, F., R. Lifran, et al. (2001). "Agent based modelling, game theory and natural resource management issues." JASSS.
Bousquet F et al (2002). Multi-agent systems and role games: collective learning processes for ecosystem management. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Box, P. (2002). Spatial Units as Agents: Making the Landscape an equal player in Agent-based Simulations. Integrating GIS and agent-based modelling techniques. H. Gimblett, Santa Fe.
Deadman, P. (1999). "Modelling individual behaviour and group performance in an intelligent agent-based simulation of the tragedy of the commons." Journal of Environmental Management.
Deffuant, G., S. Huet, et al. (2002). Agent-based simulation of organic farming conversion in Allier departement. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Duke-Sylvester, S. and L. Gross (2002). Integrating spatial data into an agent-based modelling system: Ideas and lessons from the development of the across trophic level system simulation. Integrating GIS and agent-based modelling techniques. H. Gimblett, Santa Fe.
Etienne, M. (2003). "SYLVOPAST: a multiple target role-playing game to assess negotiation processes in sylvopastroal management planning." JASSS.
Etienne, M., C. Le Page, et al. (2003). "A step-by-step approach to building land management scenarios based on multiple viewpoints on multi-agent system simulations." JASSS.
Evan, T. and H. Kelley (2004). "Multi-scale analysis of a household level agent-based model of landcover change." Journal of environmental management.
FIRMA (2003). Participatory Integrated Assessment in Five Case Studies, http://firma.cfpm.org/reports.html.
Gimblett, H. (2002). Integrating GIS and agent-based technologies for modelling and simulating social and ecological phenomena. Integrating GIS and agent-based modelling techniques. G. H, Santa Fe.
Gotts, N., J. Pollihill, et al. (2002). "Aspiration levels in a land use simulation (FEARLUS),." WIP.
Gotts, N., J. Pollihill, et al. (2002). "Dynamics of imitation in a land use simulation (FEARLUS)." WIP.
Gotts, N., J. Pollihill, et al. (2002). "FEARLUS-W: An agent-based model of river basin land use and water management,." WIP.
Hare, M. and P. Deadman (2004). "Further towards a taxonomy of agent-based simulation models in environmental management,." Mathematics and computers in simulation.
Harper, S., J. Westervelt, et al. (2002). Management Application of an agent-based model: Control of Cowbirds at the Landscape Scale. Integrating GIS and agent-based modelling techniques. H. Gimblett, Santa Fe.
Hoffman, M., H. Kelley, et al. (2002). Simulating land-cover change in South-Central Indiana: an agent-based model of deforestation and afforestation. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Huigen, M. (2004). "First principles of the MameLuke multi-actor modelling framework for land-use change, illustrated with a Philippine case study." Journal of environmental management.
Janssen, M., B. Walker, et al. (2000). "An adaptive agent model for analysing co-evolution of management and policies in a complex rangeland system,." Ecological Modelling.
Janssen, M. (2001). "An exploratory integrated model to assess management of lake eutrophication." Ecological Modelling.
Kohler T et al (1999). Be there then: A modelling approach to settlement determinants and spatial efficiency among late ancestral pueblo populations of the Messa Verde region US southwest. Dynamics in Human Primate Societies. T. Kohler and G. Gumerman.
Ligtenberg, A., M. Wachowicz, et al. (2004). "A design and application of a multi-agent system for simulation of multi-actor spatial planning." Journal of environmental management.
Lynam, T. (2002). Scientific measurements and villagers' knowledge: an integrative multi-agent model from the semi-arid areas of Zimbabwe. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Mathews, R. (2004). "PALM: An agent-based spatial model of livelihood generation and resource flows in rural households and their environment,." WIP.
Mathews, R. and C. Pilbeam (2004). "Modelling the long term sustainability of maize/millet cropping systems in the mid-hills of Nepal,." WIP.
Nute, D. (2004). "NED-2: an agent based decision support system for forest ecosystem management." Environmental modelling and software.
Otter H, d. V. A., and de Vriend H, (2001). "ABLOoM: Location behaviour, spatial patterns and agent-based modelling." JASSS.
Parker, D., T. Berger, et al., Eds. (2001). Agent-Based Models of Land-Use and Land-Cover Change: Report and Review of an International Workshop. Indiana, Indiana University.
Parker, D., S. Manson, et al. (2003). "Multi-agents systems for the simulation of land-use and land-cover change: A review." Annals of the Association of American Geographers.
Parker, D. and V. Maretsky (2004). "Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics." Agriculture, ecosystems and environment.
Rajan, K. and R. Shibasaki (1999). "Model Simulated land use/Cover changes in Thailand-results from AGENT-LUC model." www.gisdevelopment.net/aars/acrs/1999/ts5/ts5207.shtml.
Rouchier, J., F. Bousquet, et al. (2001). "A multi-agent model for describing transhumanance in North Cameroon: Comparison of different rationality to develop a routine." Journal of Economic Dynamics and Control.
Sander, L., D. Pumain, et al. (1997). "SIMPOP: a multiagent system for the study of urbanisation." Environment and Planning B.
Torrens, P. (2001). "Can geocomputation save urban simulation?" WIP.
Turner II et al (2001). "Deforestation in the southern Yucatan peninsular region: an integrative approach." Forest ecology and management.
In the Simsoc list, Dawn Parker of GMU then posted this message (2005-01-25) and a fine list of things. You list looks fairly complete. I have an extensive bibliography with some additional references available on my course web site "Spatial agent-based models of human-environment interactions":
http://mason.gmu.edu/~dparker3/spat_abm/spat_abm.html
http://mason.gmu.edu/~dparker3/spat_abm/abm_he.enl
http://mason.gmu.edu/~dparker3/spat_abm/abm_he.pdf
And, here is the complete bibliography from a forthcoming chapter, "Integration of Geographic Information Systems and Agent-Based Models of Land Use: Prospects and Challenges," forthcoming in the ESRI press book “GIS, Spatial Analysis and Modeling,†David J. Maguire, Michael F. Goodchild and Michael Batty, Editors.
There is a more complete version of this bibliography that I can send you if you like, in endnote or text format.
Agarwal, C., G. M. Green, J. M. Grove, T. Evans, and C. Schweik. 2002. A review and assessment of land-use change models: Dynamics of space, time, and human choice. Burlington, VT: USDA Forest Service Northeastern Forest Research Station Publication NE-297. http://www.fs.fed.us/ne/newtown_square/publications/technical_reports/ pdfs/2002/gtrne297.pdf.
Anas, A., R. Arnott, and K. A. Small. 1998. Urban spatial structure. Journal of Economic Literature 36 (3): 1426-1464
Angelsen, A., and D. Kaimowitz. 1998. Rethinking the causes of tropical deforestation: Lessons from economic models. The World Bank Research Observer 14 (1): 73-98. http://www.worldbank.org/research/journals/wbro/obsfeb99/pdf/ article4.pdf.
Anselin, L. 1988. Spatial econometrics: Methods and models. Kluwer Academic, Studies in Operational Regional Science series, Norwell, MA; London and Dordrecht
—. 2002. Under the hood: Issues in the specification and interpretation of spatial regression models. Agricultural Economics 27 (3): 247-267
Aquino (d'), P., C. Le Page, F. Bousquet, and A. Bah. 2003. Using self-designed role-playing games and a multi-agent system to empower a local decision-making process for land use management: The selfcormas experiment in Senegal. Journal of Artificial Societies and Social Simulation 6 (3). .
Balmann, A. 1997. Farm-based modelling of regional structural change. European Review of Agricultural Economics 25 (1): 85-108
Balmann, A., K. Happe, K. Kellermann, and A. Kleingarn. 2003. Adjustment costs of agri-environmental policy switchings: A multi-agent approach in M. A. Janssen, ed. Complexity and Ecosystem Management: The Theory and Practice of Multi-agent Approaches. Edward Elgar Publishers, Cheltenham, U.K.; Northampton, MA
Becu, N., P. Perez, B. Walker, O. Barreteau, and C. Le Page. 2003. Agent-based simulation of a small catchment water management in northern Thailand: Description of the catchscape model. Ecological Modelling 170 (2-3): 319-331
Benenson, I., S. Aronovich, and S. Noam. forthcoming. Let's talk objects: Generic methodology for urban high-resolution simulation. Computers, Environment, and Urban Systems
Benenson, I., and P. Torrens. 2004. Geosimulation: Automata-Based Modeling of Urban Phenomena. John Wiley & Sons, London
Berger, T. 2001. Agent-based spatial models applied to agriculture: A simulation tool for technology diffusion, resource use changes, and policy analysis. Agricultural Economics 25 (2-3): 245-260
Berger, T., and D. C. Parker. 2002. Introduction to Specific Examples of Research. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. CIPEC/CSISS, Santa Barbara. http://www.csiss.org/maslucc/ABM-LUCC.htm.
Berry, B. J. L., L. D. Kiel, and E. Elliot. 2002. Adaptive agents, intelligence, and emergent human organization: Capturing complexity through agent-based modeling. Proceedings of the National Academy of Sciences 99 (Supplement 3): 7178-7188
Boissau, S., and J. C. Castella. 2003. Constructing a common representation of local institutions and land use systems through simulation-gaming and multi-agent modeling in rural areas of northern Vietnam: The SAMBA-Week methodology. Simulations and Gaming 34 (3): 342-347
Bousquet, F., F. O. Barreteau, P. d'Aquino, M. Etienne, S. Boissau, S. Auber, C. L. Page, D. Babin, and J. C. Castella. 2003. Multi-agent systems and role games: An approach for ecosystem co-management in M. A. Janssen, ed. Multi-Agent Approaches for Ecosystem Management. Edward Elgar Publishers, Cheltenham, U.K.; Northampton, MA
Bousquet, F., and D. Gautier. 1998. Comparaison de deux approches de modélisation des dynamiques spatiales par simulation multi-agents : Les approches spatiales et acteurs. CyberGéo 89. http://193.55.107.45/modelis/bousquet/bousquet.htm.
Bousquet, F., and C. Le Page. 2004. Multi-agent simulations and ecosystem management: A review. Ecological Modelling 76 (3-4): 313-332
Bousquet, F., C. Le Page, M. Antona, and P. Guizol. 2000. Ecological scales and use rights: The use of multiagent systems. Paper presented in the Forest and society : The role of research. Sub-plenary session XXI. IUFRO World Congress 2000, Kuala Lumpur.
Bousquet, F., C. LePage, I. Bakam, and A. Takforyan. 2001. Multi-agent simulations of hunting wild meat in a village in eastern Cameroon. Ecological Modelling 138 (1-3): 331-346
Briassoulis, H. 1999. Analysis of Land Use Change: Theoretical and Modeling Approaches. Regional Research Institute, West Virginia University, Morgantown, WV. http://www.rri.wvu.edu/WebBook/Briassoulis/contents.htm.
Brown, D., M. North, D. Robinson, R. Riolo, and W. Rand. forthcoming-a. Spatial process and data models: Toward integration of agent-based models and GIS. Journal of Geographic Systems
Brown, D., R. Riolo, D. Robinson, W. Rand, M. North, and K. Johnston. 2004. Toward integration of spatial data models and agent-based process models. Paper presented in the GIScience 2004: Third International Conference on Geographic Information Science, University of Maryland Conference Center.
Brown, D. G., S. E. Page, R. Riolo, M. Zellner, and R. W. forthcoming-b. Path dependence and the validation of agent-based spatial models of land use. International Journal of Geographic Information Systems
Caruso, G., M. Rounsevell, and G. Cojocaru. Forthcoming. Exploring a spatio-dynamic neighbourhood-based model of residential behaviour in the Brussels periurban area. International Journal of Geographical Information Science
Deadman, P., D. Robinson, E. Moran, and E. Brondizio. forthcoming. Effects of colonist household structure on land-use change in the Amazon rainforest: An agent-based simulation approach. Environment and Planning B
Dibble, C., and P. G. Feldman. 2004. The GeoGraph 3D Computational Laboratory: Network and Terrain Landscapes for RePast. Journal of Artificial Societies and Social Simulation 7 (1). http://jasss.soc.surrey.ac.uk/7/1/7.html.
Ducrot, R., C. Le Page, P. Bommel, and M. Kuper. 2004. Articulating land and water dynamics with urbanization:an attempt to model natural resources management at the urban edge. Computers, Environment, and Urban Systems 28 (1-2): 85-106
Epstein, J. M., and R. Axtell. 1996. Growing Artificial Societies: Social Science from the Ground Up. Brookings Institution Press, Washington, D.C.
Etienne, M. 2003a. Sylvopast: A multiple target role-playing game to assess negotiation processes in sylvopastoral management planning. Journal of Artificial Societies and Social Simulation 6 (2). http://jasss.soc.surrey.ac.uk/6/2/5.html.
Etienne, M., Le Page, C. and Cohen, M. 2003b. A step-by-step approach to building land management scenarios based on multiple viewpoints on multi-agent system simulations. Journal of Artificial Societies and Social SImulation 6 (2). http://jasss.soc.surrey.ac.uk/6/2/2.html.
Evans, T. P., and H. Kelley. 2004. Multi-scale analysis of a household level agent-based model of landcover change. Journal of Environmental Management 72 (1-2): 57-72
Feuillette, S., F. Bousquet, and P. Le Goulven. 2003. Sinuse: A multi-agent model to negotiate water demand management on a free access water table. Environmental Modelling and Software 18 (5): 413-427
Fleming, M. 2004. Techniques for Estimating Spatially Dependent Discrete Choice Models in L. Anselin and R. J. G. M. Florax, eds. Advances in Spatial Econometrics. Springer, New York
Fowler, M., and K. Scott. 2000. UML Distilled: A Brief Guide to the Standard Object Modeling Laguage. Addison Wesley Longman, Reading, MA
Geist, H., and E. F. Lambin. 2002. Proximate causes and underlying driving forces of tropical deforestation. Bioscience 52 (2): 143-150
Gimblett, H. R., ed. 2002a. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
—. 2002b. Integrating Geographic Information Systems and agent-based technologies for modeling and simulating social and ecological phenomena. Pages 1-20 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Gimblett, H. R., M. T. Richards, and R. Itami. 2002. Simulating wildland recreation use and conflicting spatial interactions using rule-driven agents. Pages 211-244 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Gimblett, H. R., C. A. Roberts, T. C. Daniel, M. Ratcliff, M. Meitner, S. Cherry, D. Stallman, R. Bogle, D. K. Allerd, and J. Bieri. 2002. An intelligent agent model for simulating and evaluating river trip scenarios along the Colorado River in Grand Canyon National Park. Pages 245-276 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Gonçalves, A. S., A. Rodrigues, and L. Correia. 2004. Multi-Agent Simulation within Geographic Information Systems. Paper presented in the 5th Workshop on Agent-Based Simulation, ABS04, May, Lisbon, Portugal.
Gotts, N. M. G., J. G. Polhill, and A. N. R. Law. 2003. Aspiration levels in a land use simulation. Cybernetics and Systems 34 (8): 663-683
Grimm, V., and S. F. Railsback. forthcoming. Chapter 1: Introduction in V. Grimm and S. F. Railsback, eds. Individual-based Modeling and Ecology. Princeton University Press, Princeton, NJ
Harper, S. J., J. D. Westervelt, and A.-M. Trame. 2002. Management application of an agent-based model: Control of cowbirds at the landscape scale in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Irwin, E., and N. Bockstael. 2002. Interacting agents, spatial externalities, and the evolution of residential land use patterns. Journal of Economic Geography 2 (1): 31-54
Irwin, E. G., and N. Bockstael. forthcoming. The spatial pattern of land use in the U.S. in R. Arnott and D. McMillen, eds. A Companion to Urban Economics
Itami, R. 2002. Mobile agents with spatial intelligence. Pages 191-210 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Itami, R., R. Raulings, G. MacLaren, K. Hirst, R. Gimblett, D. Zanon, and P. Chladek. 2004. Simulating the complex interactions between human movement and the outdoor recreation environment. Journal of Nature Conservation 11 (4): 278-286
Itami, R. M., G. S. MacLaren, K. M. Hirst, R. J. Raulings, and H. R. Gimblett. 2000. RBSIM 2: Simulating human behavior in National Parks in Australia: Integrating GIS and Intelligent Agents to predict recreation conflicts in high use natural environments. Paper presented in the 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), September 2 - 8, Banff, Alberta, Canada. http://www.colorado.edu/research/cires/banff/pubpapers/57/.
Jackson, R. W. 1994. Object-oriented modeling in regional science: An advocacy view. Papers in Regional Science 73 (4): 347-367
Janssen, M. A., ed. 2003. Complexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches. Edward Elgar Publishers, Cheltenham, U.K.; Northampton, MA
Janssen, M. A., and E. Ostrom. forthcoming. Governing social-ecological systems in K. Judd and L. Tesfatsion, eds. Handbook of Computational Economics II: Agent-Based Computational Economics. North-Holland
Kaimowitz, D., and A. Angelsen. 1998. Economic Models of Tropical Deforestation: A Review. Centre for International Forestry Research, Jakarta, Indonesia
Kohler, T. A., J. Kresl, C. V. West, E. Carr, and R. H. Wilshusen. 2000. Be there then: A modeling approach to settlement determinants and spatial efficiency among late ancestral pueblo populations of the Mesa Verde region, U.S. Southwest. Pages 145-178 in T. A. Kohler and G. J. Gumerman, eds. Dynamics in Human and Primate Societies. Oxford University Press, New York and Oxford, U.K.
Kwartler, M., and R. N. Bernard. 2001. CommunityViz: An Integrated Planning Support System in R. K. Brail and R. E. Klosterman, eds. Planning Support Systems Integrating Geographic Systems, Models, and Visualization Tools. ESRI Press, Redland, CA
Lambin, E. F., H. Geist, and E. Lepers. 2003. Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environmental Resources 28: 205-241
Long, J. S. 1997. Regression Models for Categorical and Limited Dependent Variables. Sage Publications, Thousand Oaks, CA
Luke, S., G. C. Balan, L. Panait, C. Cioffi-Revilla, and S. Paus. 2003. MASON: A Java multi-agent simulation library. Paper presented in the Agent 2003 conference: Challenges in social simulation, Chicago, IL. http://agent2003.anl.gov/proc.html.
Manson, S. M. 2000. Agent-based dynamic spatial simulation of land-use/cover change in the Yucatán peninsula, Mexico. Paper presented in the Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Banff, Canada. http://www.tc.umn.edu/~manson/Resources/Manson_2000_GISEM4_ADSS_www.pdf.
—. 2002. Integrated Assessment and Projection of Land-Use and Land-Cover Change in the Southern Yucatán Peninsular Region of Mexico. Ph D. diss. Clark, Worcester, MA
—. forthcoming. The SYPR integrative assessment model: Complexity in development in B. L. Turner II, D. Foster, and J. Geoghegan, eds. Final Frontiers: Understanding Land Change in the Southern Yucatán Peninsular Region. Claredon Oxford University Press, Oxford, UK
Mathevet, R., F. Bousquet, C. Le Page, and M. Antona. 2003. Agent-based simulations of interactions between duck populations, farming decisions and leasing of hunting rights in the Camargue (Southern France). Ecological Modelling 165 (2-3): 107-126
McGarigal, K., and B. J. Marks. 1994. FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station Publication Gen. Tech. Rep. PNW-GTR-351.
Najlis, R. 2004. Personal Communication: Technical specifications for the TSUNAMI and Agent Analyst models.
Najlis, R., and M. North. 2004. Repast for GIS. Paper presented in the Agent 2004 Conference on Social Dynamics: Interaction, Reflexivity, and Emergence, Chicago, IL. http://agent2004.anl.gov/proc.html.
Najlis, R. I., M. A. Janssen, and D. C. Parker. 2002. Software tools and communication issues. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. CIPEC/CSISS, Santa Barbara. http://www.csiss.org/maslucc/ABM-LUCC.htm.
North, M., M. Rimmer, and C. M. Macal. 2003. Why the Navy Needs TSUNAMI. Paper presented in the Swarmfest 2003, South Bend, IN.
Parker, D. C., T. Berger, and S. M. Manson. 2002a. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. Santa Barbara: CIPEC/CSISS Publication CCR-3. http://www.csiss.org/maslucc/ABM-LUCC.htm.
—. 2002b. Agent-Based Models of Land-Use/Land-Cover Change: Report and Review of an International Workshop. Bloomington, IN: LUCC Focus 1 Publication 6. http://www.indiana.edu/~act/focus1/FinalABM11.7.02.pdf.
Parker, D. C., S. M. Manson, and T. Berger. 2002. POTENTIAL STRENGTHS AND APPROPRIATE ROLES FOR ABM/LUCC. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. CIPEC/CSISS, Santa Barbara. http://www.csiss.org/maslucc/ABM-LUCC.htm.
Parker, D. C., S. M. Manson, M. A. Janssen, M. Hoffmann, and P. Deadman. 2003. Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers 93 (2): 314–337
Parker, D. C., and V. Meretsky. 2004. Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agriculture, Ecosystems and Environment 101 (2-3): 233-250
Parker, M. T. 2001. What is Ascape and why should you care? Journal of Artificial Societies and Social SImulation 4 (1). http://jasss.soc.surrey.ac.uk/4/1/5.html.
Perman, R., Y. Ma, J. McGilvray, and M. Common. 2003. Natural Resource and Environmental Economics. Pearson Addison Wesley, New York
Reynolds, R., T. A. Kohler, and Z. Kobti. 2003. The effects of generalized reciprocal exchange on the resilience of social networks: An example from the Prehispanic Mesa Verde region. Computational & Mathematical Organization Theory 9 (3): 227-254
Thomas, W. H., M. North, C. M. Macal, and J. P. Peerenboom. 2003. From physics to finances: Complex adaptive systems representation of infrastructure interdependencies. Dahlgren, VA: Naval Surface Warfare Center Publication
Torrens, P. 2003. Automata-based models of urban systems. Pages 61-81 in P. A. Longley and M. Batty, eds. Advanced Spatial Analysis. ESRI press, Redlands, CA
Torrens, P., and I. Benenson. forthcoming. Geographic Automata Systems. International Journal of Geographic Information Systems
Trébuil, G., F. Shinawtra-Ekasingh, F. Bousquet, and C. Thong-Ngam. 2002. Multi-agent systems companion modeling for integrated watershed management: A Northern Thailand experience. Paper presented in the 3rd International Conference on Montane Mainland Southeast Asia (MMSEA 3), Lijiang, Yunnan, China.
Verburg, P. H., P. Schot, M. Dijst, and A. Velkamp. forthcoming. Land-use change modeling: Current practice and research priorities. GeoJournal
Westervelt, J. 2002. Geographic information systems and agent-based modeling in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes. Oxford University Press, Oxofrd, U.K.
Westervelt, J. D., and L. D. Hopkins. 1999. Modeling mobile individuals in dynamic landscapes. International Journal of Geographic Information Systems 13 (3): 191-208
Leigh Tesfatsion added
Below is an article that would seem to fit well with your objectives but that is not on your list:
J. Stephen Lansing and James N. Kremer, "Emergent Properties of Balinese Water Temple Networks: Coadaptation on a Rugged Fitness Landscape," American Anthropologist, New Series, Vol. 95, No. 1, March 1993, 97-114.
Bob Axelrod and I list this on our Guide for Newcomers to Agent-Based Modeling in the Social Sciences (http://www.econ.iastate.edu/tesfatsi/abmread.htm).
From the simsoc list 1/27/2005, Dimitris Ballas
The Joseph Rowntree Foundation has just published a guide to the development of microsimulation techniques in research.
Geography matters, by Dimitris Ballas of the University of Sheffield (and others), builds on past work in the area of microsimulation to present a new spatial simulation methodology. It discusses the conceptual and practical issues of microsimulation, highlighting the differences between static and dynamic microsimulation. The authors outline how a geographical microsimulation model can be built and explain the geographical simulation method clearly, keeping mathematical and statistical jargon to a minimum.
The book promotes greater convergence of the methods used by economists, geographers and other social scientists working in this field. It will appeal to all social scientists and researchers interested in the geographical implications of social policies and will be a useful introduction for undergraduate and postgraduate students to simulation methods in the social sciences.
Geography matters is available now as a free PDF download or as a paperback report, priced £17.95, from http://www.jrf.org.uk/bookshop/details.asp?pubID=659.
If you know of any relevant models we have not included please could you email the details to us at ablum@hotmail.co.uk. We will update the list and hopefully leave a useful resource for anyone interested in this topic.
Many thanks for your help,
Dr Robin Matthews and Alan Roach
Agent Based Land Use Models Reference List
Axtell R et al (1999). Understanding Anasazi Culture Change Through Agent-Based Modelling. Dynamics in Human Primate Societies. T. Kohler and G. Gumerman.
Balmann, A., K. Happe, et al. (2003). Adjustment costs of agri-environmental policy switching: an agent-based analysis of the German region Hohenlohe. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Barreteau, O. and F. Bousquet (2000). "SHADOC; a multi-agent model to tackle viability of irrigated systems,." Annals of operations research.
Becu, N., P. Perez, et al. (2003). "Agent based simulation of a small catchment water management in northern Thailand: description of the CATCHSCAPE model." Ecological Modelling.
Berger, T. (2001). "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis." Agricultural economics.
Bousquet, F. and C. Page ( 2004). "Multi-agent simulations and ecosystem management: a review,." Ecological Modelling.
Bousquet, F., R. Lifran, et al. (2001). "Agent based modelling, game theory and natural resource management issues." JASSS.
Bousquet F et al (2002). Multi-agent systems and role games: collective learning processes for ecosystem management. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Box, P. (2002). Spatial Units as Agents: Making the Landscape an equal player in Agent-based Simulations. Integrating GIS and agent-based modelling techniques. H. Gimblett, Santa Fe.
Deadman, P. (1999). "Modelling individual behaviour and group performance in an intelligent agent-based simulation of the tragedy of the commons." Journal of Environmental Management.
Deffuant, G., S. Huet, et al. (2002). Agent-based simulation of organic farming conversion in Allier departement. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Duke-Sylvester, S. and L. Gross (2002). Integrating spatial data into an agent-based modelling system: Ideas and lessons from the development of the across trophic level system simulation. Integrating GIS and agent-based modelling techniques. H. Gimblett, Santa Fe.
Etienne, M. (2003). "SYLVOPAST: a multiple target role-playing game to assess negotiation processes in sylvopastroal management planning." JASSS.
Etienne, M., C. Le Page, et al. (2003). "A step-by-step approach to building land management scenarios based on multiple viewpoints on multi-agent system simulations." JASSS.
Evan, T. and H. Kelley (2004). "Multi-scale analysis of a household level agent-based model of landcover change." Journal of environmental management.
FIRMA (2003). Participatory Integrated Assessment in Five Case Studies, http://firma.cfpm.org/reports.html.
Gimblett, H. (2002). Integrating GIS and agent-based technologies for modelling and simulating social and ecological phenomena. Integrating GIS and agent-based modelling techniques. G. H, Santa Fe.
Gotts, N., J. Pollihill, et al. (2002). "Aspiration levels in a land use simulation (FEARLUS),." WIP.
Gotts, N., J. Pollihill, et al. (2002). "Dynamics of imitation in a land use simulation (FEARLUS)." WIP.
Gotts, N., J. Pollihill, et al. (2002). "FEARLUS-W: An agent-based model of river basin land use and water management,." WIP.
Hare, M. and P. Deadman (2004). "Further towards a taxonomy of agent-based simulation models in environmental management,." Mathematics and computers in simulation.
Harper, S., J. Westervelt, et al. (2002). Management Application of an agent-based model: Control of Cowbirds at the Landscape Scale. Integrating GIS and agent-based modelling techniques. H. Gimblett, Santa Fe.
Hoffman, M., H. Kelley, et al. (2002). Simulating land-cover change in South-Central Indiana: an agent-based model of deforestation and afforestation. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Huigen, M. (2004). "First principles of the MameLuke multi-actor modelling framework for land-use change, illustrated with a Philippine case study." Journal of environmental management.
Janssen, M., B. Walker, et al. (2000). "An adaptive agent model for analysing co-evolution of management and policies in a complex rangeland system,." Ecological Modelling.
Janssen, M. (2001). "An exploratory integrated model to assess management of lake eutrophication." Ecological Modelling.
Kohler T et al (1999). Be there then: A modelling approach to settlement determinants and spatial efficiency among late ancestral pueblo populations of the Messa Verde region US southwest. Dynamics in Human Primate Societies. T. Kohler and G. Gumerman.
Ligtenberg, A., M. Wachowicz, et al. (2004). "A design and application of a multi-agent system for simulation of multi-actor spatial planning." Journal of environmental management.
Lynam, T. (2002). Scientific measurements and villagers' knowledge: an integrative multi-agent model from the semi-arid areas of Zimbabwe. Complexity and ecosystem management: The theory and practice of multiagent systems. M. Janessen.
Mathews, R. (2004). "PALM: An agent-based spatial model of livelihood generation and resource flows in rural households and their environment,." WIP.
Mathews, R. and C. Pilbeam (2004). "Modelling the long term sustainability of maize/millet cropping systems in the mid-hills of Nepal,." WIP.
Nute, D. (2004). "NED-2: an agent based decision support system for forest ecosystem management." Environmental modelling and software.
Otter H, d. V. A., and de Vriend H, (2001). "ABLOoM: Location behaviour, spatial patterns and agent-based modelling." JASSS.
Parker, D., T. Berger, et al., Eds. (2001). Agent-Based Models of Land-Use and Land-Cover Change: Report and Review of an International Workshop. Indiana, Indiana University.
Parker, D., S. Manson, et al. (2003). "Multi-agents systems for the simulation of land-use and land-cover change: A review." Annals of the Association of American Geographers.
Parker, D. and V. Maretsky (2004). "Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics." Agriculture, ecosystems and environment.
Rajan, K. and R. Shibasaki (1999). "Model Simulated land use/Cover changes in Thailand-results from AGENT-LUC model." www.gisdevelopment.net/aars/acrs/1999/ts5/ts5207.shtml.
Rouchier, J., F. Bousquet, et al. (2001). "A multi-agent model for describing transhumanance in North Cameroon: Comparison of different rationality to develop a routine." Journal of Economic Dynamics and Control.
Sander, L., D. Pumain, et al. (1997). "SIMPOP: a multiagent system for the study of urbanisation." Environment and Planning B.
Torrens, P. (2001). "Can geocomputation save urban simulation?" WIP.
Turner II et al (2001). "Deforestation in the southern Yucatan peninsular region: an integrative approach." Forest ecology and management.
In the Simsoc list, Dawn Parker of GMU then posted this message (2005-01-25) and a fine list of things. You list looks fairly complete. I have an extensive bibliography with some additional references available on my course web site "Spatial agent-based models of human-environment interactions":
http://mason.gmu.edu/~dparker3/spat_abm/spat_abm.html
http://mason.gmu.edu/~dparker3/spat_abm/abm_he.enl
http://mason.gmu.edu/~dparker3/spat_abm/abm_he.pdf
And, here is the complete bibliography from a forthcoming chapter, "Integration of Geographic Information Systems and Agent-Based Models of Land Use: Prospects and Challenges," forthcoming in the ESRI press book “GIS, Spatial Analysis and Modeling,†David J. Maguire, Michael F. Goodchild and Michael Batty, Editors.
There is a more complete version of this bibliography that I can send you if you like, in endnote or text format.
Agarwal, C., G. M. Green, J. M. Grove, T. Evans, and C. Schweik. 2002. A review and assessment of land-use change models: Dynamics of space, time, and human choice. Burlington, VT: USDA Forest Service Northeastern Forest Research Station Publication NE-297. http://www.fs.fed.us/ne/newtown_square/publications/technical_reports/ pdfs/2002/gtrne297.pdf.
Anas, A., R. Arnott, and K. A. Small. 1998. Urban spatial structure. Journal of Economic Literature 36 (3): 1426-1464
Angelsen, A., and D. Kaimowitz. 1998. Rethinking the causes of tropical deforestation: Lessons from economic models. The World Bank Research Observer 14 (1): 73-98. http://www.worldbank.org/research/journals/wbro/obsfeb99/pdf/ article4.pdf.
Anselin, L. 1988. Spatial econometrics: Methods and models. Kluwer Academic, Studies in Operational Regional Science series, Norwell, MA; London and Dordrecht
—. 2002. Under the hood: Issues in the specification and interpretation of spatial regression models. Agricultural Economics 27 (3): 247-267
Aquino (d'), P., C. Le Page, F. Bousquet, and A. Bah. 2003. Using self-designed role-playing games and a multi-agent system to empower a local decision-making process for land use management: The selfcormas experiment in Senegal. Journal of Artificial Societies and Social Simulation 6 (3). .
Balmann, A. 1997. Farm-based modelling of regional structural change. European Review of Agricultural Economics 25 (1): 85-108
Balmann, A., K. Happe, K. Kellermann, and A. Kleingarn. 2003. Adjustment costs of agri-environmental policy switchings: A multi-agent approach in M. A. Janssen, ed. Complexity and Ecosystem Management: The Theory and Practice of Multi-agent Approaches. Edward Elgar Publishers, Cheltenham, U.K.; Northampton, MA
Becu, N., P. Perez, B. Walker, O. Barreteau, and C. Le Page. 2003. Agent-based simulation of a small catchment water management in northern Thailand: Description of the catchscape model. Ecological Modelling 170 (2-3): 319-331
Benenson, I., S. Aronovich, and S. Noam. forthcoming. Let's talk objects: Generic methodology for urban high-resolution simulation. Computers, Environment, and Urban Systems
Benenson, I., and P. Torrens. 2004. Geosimulation: Automata-Based Modeling of Urban Phenomena. John Wiley & Sons, London
Berger, T. 2001. Agent-based spatial models applied to agriculture: A simulation tool for technology diffusion, resource use changes, and policy analysis. Agricultural Economics 25 (2-3): 245-260
Berger, T., and D. C. Parker. 2002. Introduction to Specific Examples of Research. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. CIPEC/CSISS, Santa Barbara. http://www.csiss.org/maslucc/ABM-LUCC.htm.
Berry, B. J. L., L. D. Kiel, and E. Elliot. 2002. Adaptive agents, intelligence, and emergent human organization: Capturing complexity through agent-based modeling. Proceedings of the National Academy of Sciences 99 (Supplement 3): 7178-7188
Boissau, S., and J. C. Castella. 2003. Constructing a common representation of local institutions and land use systems through simulation-gaming and multi-agent modeling in rural areas of northern Vietnam: The SAMBA-Week methodology. Simulations and Gaming 34 (3): 342-347
Bousquet, F., F. O. Barreteau, P. d'Aquino, M. Etienne, S. Boissau, S. Auber, C. L. Page, D. Babin, and J. C. Castella. 2003. Multi-agent systems and role games: An approach for ecosystem co-management in M. A. Janssen, ed. Multi-Agent Approaches for Ecosystem Management. Edward Elgar Publishers, Cheltenham, U.K.; Northampton, MA
Bousquet, F., and D. Gautier. 1998. Comparaison de deux approches de modélisation des dynamiques spatiales par simulation multi-agents : Les approches spatiales et acteurs. CyberGéo 89. http://193.55.107.45/modelis/bousquet/bousquet.htm.
Bousquet, F., and C. Le Page. 2004. Multi-agent simulations and ecosystem management: A review. Ecological Modelling 76 (3-4): 313-332
Bousquet, F., C. Le Page, M. Antona, and P. Guizol. 2000. Ecological scales and use rights: The use of multiagent systems. Paper presented in the Forest and society : The role of research. Sub-plenary session XXI. IUFRO World Congress 2000, Kuala Lumpur.
Bousquet, F., C. LePage, I. Bakam, and A. Takforyan. 2001. Multi-agent simulations of hunting wild meat in a village in eastern Cameroon. Ecological Modelling 138 (1-3): 331-346
Briassoulis, H. 1999. Analysis of Land Use Change: Theoretical and Modeling Approaches. Regional Research Institute, West Virginia University, Morgantown, WV. http://www.rri.wvu.edu/WebBook/Briassoulis/contents.htm.
Brown, D., M. North, D. Robinson, R. Riolo, and W. Rand. forthcoming-a. Spatial process and data models: Toward integration of agent-based models and GIS. Journal of Geographic Systems
Brown, D., R. Riolo, D. Robinson, W. Rand, M. North, and K. Johnston. 2004. Toward integration of spatial data models and agent-based process models. Paper presented in the GIScience 2004: Third International Conference on Geographic Information Science, University of Maryland Conference Center.
Brown, D. G., S. E. Page, R. Riolo, M. Zellner, and R. W. forthcoming-b. Path dependence and the validation of agent-based spatial models of land use. International Journal of Geographic Information Systems
Caruso, G., M. Rounsevell, and G. Cojocaru. Forthcoming. Exploring a spatio-dynamic neighbourhood-based model of residential behaviour in the Brussels periurban area. International Journal of Geographical Information Science
Deadman, P., D. Robinson, E. Moran, and E. Brondizio. forthcoming. Effects of colonist household structure on land-use change in the Amazon rainforest: An agent-based simulation approach. Environment and Planning B
Dibble, C., and P. G. Feldman. 2004. The GeoGraph 3D Computational Laboratory: Network and Terrain Landscapes for RePast. Journal of Artificial Societies and Social Simulation 7 (1). http://jasss.soc.surrey.ac.uk/7/1/7.html.
Ducrot, R., C. Le Page, P. Bommel, and M. Kuper. 2004. Articulating land and water dynamics with urbanization:an attempt to model natural resources management at the urban edge. Computers, Environment, and Urban Systems 28 (1-2): 85-106
Epstein, J. M., and R. Axtell. 1996. Growing Artificial Societies: Social Science from the Ground Up. Brookings Institution Press, Washington, D.C.
Etienne, M. 2003a. Sylvopast: A multiple target role-playing game to assess negotiation processes in sylvopastoral management planning. Journal of Artificial Societies and Social Simulation 6 (2). http://jasss.soc.surrey.ac.uk/6/2/5.html.
Etienne, M., Le Page, C. and Cohen, M. 2003b. A step-by-step approach to building land management scenarios based on multiple viewpoints on multi-agent system simulations. Journal of Artificial Societies and Social SImulation 6 (2). http://jasss.soc.surrey.ac.uk/6/2/2.html.
Evans, T. P., and H. Kelley. 2004. Multi-scale analysis of a household level agent-based model of landcover change. Journal of Environmental Management 72 (1-2): 57-72
Feuillette, S., F. Bousquet, and P. Le Goulven. 2003. Sinuse: A multi-agent model to negotiate water demand management on a free access water table. Environmental Modelling and Software 18 (5): 413-427
Fleming, M. 2004. Techniques for Estimating Spatially Dependent Discrete Choice Models in L. Anselin and R. J. G. M. Florax, eds. Advances in Spatial Econometrics. Springer, New York
Fowler, M., and K. Scott. 2000. UML Distilled: A Brief Guide to the Standard Object Modeling Laguage. Addison Wesley Longman, Reading, MA
Geist, H., and E. F. Lambin. 2002. Proximate causes and underlying driving forces of tropical deforestation. Bioscience 52 (2): 143-150
Gimblett, H. R., ed. 2002a. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
—. 2002b. Integrating Geographic Information Systems and agent-based technologies for modeling and simulating social and ecological phenomena. Pages 1-20 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Gimblett, H. R., M. T. Richards, and R. Itami. 2002. Simulating wildland recreation use and conflicting spatial interactions using rule-driven agents. Pages 211-244 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Gimblett, H. R., C. A. Roberts, T. C. Daniel, M. Ratcliff, M. Meitner, S. Cherry, D. Stallman, R. Bogle, D. K. Allerd, and J. Bieri. 2002. An intelligent agent model for simulating and evaluating river trip scenarios along the Colorado River in Grand Canyon National Park. Pages 245-276 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Gonçalves, A. S., A. Rodrigues, and L. Correia. 2004. Multi-Agent Simulation within Geographic Information Systems. Paper presented in the 5th Workshop on Agent-Based Simulation, ABS04, May, Lisbon, Portugal.
Gotts, N. M. G., J. G. Polhill, and A. N. R. Law. 2003. Aspiration levels in a land use simulation. Cybernetics and Systems 34 (8): 663-683
Grimm, V., and S. F. Railsback. forthcoming. Chapter 1: Introduction in V. Grimm and S. F. Railsback, eds. Individual-based Modeling and Ecology. Princeton University Press, Princeton, NJ
Harper, S. J., J. D. Westervelt, and A.-M. Trame. 2002. Management application of an agent-based model: Control of cowbirds at the landscape scale in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Irwin, E., and N. Bockstael. 2002. Interacting agents, spatial externalities, and the evolution of residential land use patterns. Journal of Economic Geography 2 (1): 31-54
Irwin, E. G., and N. Bockstael. forthcoming. The spatial pattern of land use in the U.S. in R. Arnott and D. McMillen, eds. A Companion to Urban Economics
Itami, R. 2002. Mobile agents with spatial intelligence. Pages 191-210 in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes. Oxford University Press, Oxford, U.K.
Itami, R., R. Raulings, G. MacLaren, K. Hirst, R. Gimblett, D. Zanon, and P. Chladek. 2004. Simulating the complex interactions between human movement and the outdoor recreation environment. Journal of Nature Conservation 11 (4): 278-286
Itami, R. M., G. S. MacLaren, K. M. Hirst, R. J. Raulings, and H. R. Gimblett. 2000. RBSIM 2: Simulating human behavior in National Parks in Australia: Integrating GIS and Intelligent Agents to predict recreation conflicts in high use natural environments. Paper presented in the 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), September 2 - 8, Banff, Alberta, Canada. http://www.colorado.edu/research/cires/banff/pubpapers/57/.
Jackson, R. W. 1994. Object-oriented modeling in regional science: An advocacy view. Papers in Regional Science 73 (4): 347-367
Janssen, M. A., ed. 2003. Complexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches. Edward Elgar Publishers, Cheltenham, U.K.; Northampton, MA
Janssen, M. A., and E. Ostrom. forthcoming. Governing social-ecological systems in K. Judd and L. Tesfatsion, eds. Handbook of Computational Economics II: Agent-Based Computational Economics. North-Holland
Kaimowitz, D., and A. Angelsen. 1998. Economic Models of Tropical Deforestation: A Review. Centre for International Forestry Research, Jakarta, Indonesia
Kohler, T. A., J. Kresl, C. V. West, E. Carr, and R. H. Wilshusen. 2000. Be there then: A modeling approach to settlement determinants and spatial efficiency among late ancestral pueblo populations of the Mesa Verde region, U.S. Southwest. Pages 145-178 in T. A. Kohler and G. J. Gumerman, eds. Dynamics in Human and Primate Societies. Oxford University Press, New York and Oxford, U.K.
Kwartler, M., and R. N. Bernard. 2001. CommunityViz: An Integrated Planning Support System in R. K. Brail and R. E. Klosterman, eds. Planning Support Systems Integrating Geographic Systems, Models, and Visualization Tools. ESRI Press, Redland, CA
Lambin, E. F., H. Geist, and E. Lepers. 2003. Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environmental Resources 28: 205-241
Long, J. S. 1997. Regression Models for Categorical and Limited Dependent Variables. Sage Publications, Thousand Oaks, CA
Luke, S., G. C. Balan, L. Panait, C. Cioffi-Revilla, and S. Paus. 2003. MASON: A Java multi-agent simulation library. Paper presented in the Agent 2003 conference: Challenges in social simulation, Chicago, IL. http://agent2003.anl.gov/proc.html.
Manson, S. M. 2000. Agent-based dynamic spatial simulation of land-use/cover change in the Yucatán peninsula, Mexico. Paper presented in the Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Banff, Canada. http://www.tc.umn.edu/~manson/Resources/Manson_2000_GISEM4_ADSS_www.pdf.
—. 2002. Integrated Assessment and Projection of Land-Use and Land-Cover Change in the Southern Yucatán Peninsular Region of Mexico. Ph D. diss. Clark, Worcester, MA
—. forthcoming. The SYPR integrative assessment model: Complexity in development in B. L. Turner II, D. Foster, and J. Geoghegan, eds. Final Frontiers: Understanding Land Change in the Southern Yucatán Peninsular Region. Claredon Oxford University Press, Oxford, UK
Mathevet, R., F. Bousquet, C. Le Page, and M. Antona. 2003. Agent-based simulations of interactions between duck populations, farming decisions and leasing of hunting rights in the Camargue (Southern France). Ecological Modelling 165 (2-3): 107-126
McGarigal, K., and B. J. Marks. 1994. FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station Publication Gen. Tech. Rep. PNW-GTR-351.
Najlis, R. 2004. Personal Communication: Technical specifications for the TSUNAMI and Agent Analyst models.
Najlis, R., and M. North. 2004. Repast for GIS. Paper presented in the Agent 2004 Conference on Social Dynamics: Interaction, Reflexivity, and Emergence, Chicago, IL. http://agent2004.anl.gov/proc.html.
Najlis, R. I., M. A. Janssen, and D. C. Parker. 2002. Software tools and communication issues. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. CIPEC/CSISS, Santa Barbara. http://www.csiss.org/maslucc/ABM-LUCC.htm.
North, M., M. Rimmer, and C. M. Macal. 2003. Why the Navy Needs TSUNAMI. Paper presented in the Swarmfest 2003, South Bend, IN.
Parker, D. C., T. Berger, and S. M. Manson. 2002a. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. Santa Barbara: CIPEC/CSISS Publication CCR-3. http://www.csiss.org/maslucc/ABM-LUCC.htm.
—. 2002b. Agent-Based Models of Land-Use/Land-Cover Change: Report and Review of an International Workshop. Bloomington, IN: LUCC Focus 1 Publication 6. http://www.indiana.edu/~act/focus1/FinalABM11.7.02.pdf.
Parker, D. C., S. M. Manson, and T. Berger. 2002. POTENTIAL STRENGTHS AND APPROPRIATE ROLES FOR ABM/LUCC. Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change. CIPEC/CSISS, Santa Barbara. http://www.csiss.org/maslucc/ABM-LUCC.htm.
Parker, D. C., S. M. Manson, M. A. Janssen, M. Hoffmann, and P. Deadman. 2003. Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers 93 (2): 314–337
Parker, D. C., and V. Meretsky. 2004. Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agriculture, Ecosystems and Environment 101 (2-3): 233-250
Parker, M. T. 2001. What is Ascape and why should you care? Journal of Artificial Societies and Social SImulation 4 (1). http://jasss.soc.surrey.ac.uk/4/1/5.html.
Perman, R., Y. Ma, J. McGilvray, and M. Common. 2003. Natural Resource and Environmental Economics. Pearson Addison Wesley, New York
Reynolds, R., T. A. Kohler, and Z. Kobti. 2003. The effects of generalized reciprocal exchange on the resilience of social networks: An example from the Prehispanic Mesa Verde region. Computational & Mathematical Organization Theory 9 (3): 227-254
Thomas, W. H., M. North, C. M. Macal, and J. P. Peerenboom. 2003. From physics to finances: Complex adaptive systems representation of infrastructure interdependencies. Dahlgren, VA: Naval Surface Warfare Center Publication
Torrens, P. 2003. Automata-based models of urban systems. Pages 61-81 in P. A. Longley and M. Batty, eds. Advanced Spatial Analysis. ESRI press, Redlands, CA
Torrens, P., and I. Benenson. forthcoming. Geographic Automata Systems. International Journal of Geographic Information Systems
Trébuil, G., F. Shinawtra-Ekasingh, F. Bousquet, and C. Thong-Ngam. 2002. Multi-agent systems companion modeling for integrated watershed management: A Northern Thailand experience. Paper presented in the 3rd International Conference on Montane Mainland Southeast Asia (MMSEA 3), Lijiang, Yunnan, China.
Verburg, P. H., P. Schot, M. Dijst, and A. Velkamp. forthcoming. Land-use change modeling: Current practice and research priorities. GeoJournal
Westervelt, J. 2002. Geographic information systems and agent-based modeling in H. R. Gimblett, ed. Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes. Oxford University Press, Oxofrd, U.K.
Westervelt, J. D., and L. D. Hopkins. 1999. Modeling mobile individuals in dynamic landscapes. International Journal of Geographic Information Systems 13 (3): 191-208
Leigh Tesfatsion added
Below is an article that would seem to fit well with your objectives but that is not on your list:
J. Stephen Lansing and James N. Kremer, "Emergent Properties of Balinese Water Temple Networks: Coadaptation on a Rugged Fitness Landscape," American Anthropologist, New Series, Vol. 95, No. 1, March 1993, 97-114.
Bob Axelrod and I list this on our Guide for Newcomers to Agent-Based Modeling in the Social Sciences (http://www.econ.iastate.edu/tesfatsi/abmread.htm).
From the simsoc list 1/27/2005, Dimitris Ballas
The Joseph Rowntree Foundation has just published a guide to the development of microsimulation techniques in research.
Geography matters, by Dimitris Ballas of the University of Sheffield (and others), builds on past work in the area of microsimulation to present a new spatial simulation methodology. It discusses the conceptual and practical issues of microsimulation, highlighting the differences between static and dynamic microsimulation. The authors outline how a geographical microsimulation model can be built and explain the geographical simulation method clearly, keeping mathematical and statistical jargon to a minimum.
The book promotes greater convergence of the methods used by economists, geographers and other social scientists working in this field. It will appeal to all social scientists and researchers interested in the geographical implications of social policies and will be a useful introduction for undergraduate and postgraduate students to simulation methods in the social sciences.
Geography matters is available now as a free PDF download or as a paperback report, priced £17.95, from http://www.jrf.org.uk/bookshop/details.asp?pubID=659.
2009年6月10日星期三
Individual-Based Models
http://www.red3d.com/cwr/ibm.html
an annotated list of links
by Craig Reynolds
Individual-based models are simulations based on the global consequences of local interactions of members of a population. These individuals might represent plants and animals in ecosystems, vehicles in traffic, people in crowds, or autonomous characters in animation and games. These models typically consist of an environment or framework in which the interactions occur and some number of individuals defined in terms of their behaviors (procedural rules) and characteristic parameters. In an individual-based model, the characteristics of each individual are tracked through time. This stands in contrast to modeling techniques where the characteristics of the population are averaged together and the model attempts to simulate changes in these averaged characteristics for the whole population. Individual-based models are also known as entity or agent based models, and as individual/entity/agent-based simulations.
Some individual-based models are also spatially explicit meaning that the individuals are associated with a location in geometrical space. Some spatially explicit individual-based models also exhibit mobility, where the individuals can move around their environment. This would be a natural model, for example, of an animal in an ecological simulation. Whereas plants in the same simulation would not be mobile. Some individual-based models are not spatially explicit, for example a simulation of a computer network might be based on individual models of the networked computers, but their location would be irrelevant. Spatially explicit models may use either continuous (real valued) or discrete (integer valued, grid-like) space.
Individual-based models are a subset of multi-agent systems which includes any computational system whose design is fundamentally composed of a collection of interacting parts. For example an "expert system" might be composed of many distinct bits of advice which interact to produce a solution. Individual-based models are distinguished by the fact that each "agent" corresponds to autonomous individual in the simulated domain.
There is an overlap between individual-based models and cellular automata. Certainly cellular automata are similar to spatially-explicit, grid-based, immobile individual-based models. However CAs are always homogeneous and dense (all cells are identical), whereas a grid-based individual-based model might occupy only a few grid cells, and more than one distinct type of individual might live on the same grid. (Of course a CA can have cells in various states, and so represent concepts like empty or occupied by type 3. Perhaps the significant difference is whether the simulation's inner loop proceeds cell by cell, or individual by individual. (Although that distinction is muddied by parallel-processing hardware.)) The philosophical issue is whether the simulation is based on a dense and uniform dissection of the space (as in a CA), or based on specific individuals distributed within the space.
Of course, note that everyone uses terminology differently, so take the definitions above with a grain of salt. ("Your mileage may differ.")
My interest in this area began when I made a model of bird flocks and related group motion. As a result I am particularly interested in individual-based models using spatially explicit mobile agents in continuous space. This bias may be reflected in the selection of resources listed below.
Online resources
These are general purpose software toolkits useful for implementing individual-based models.
Swarm is a software package for multi-agent simulation of complex systems originally developed at The Santa Fe Institute and now at the Swarm Development Group (SDG). See this preliminary version of the Swarm FAQ and these example applications built using the Swarm system.
Echo, conceived by John Holland, is a ecology simulation framework, whose individuals live in a discrete spatially-explicit world and evolve according to a genetic algorithm. See Modelling Complex Adaptive Systems with Echo (1995) by Terry Jones and Stephanie Forrest
XRaptor (A Simulation Environment for Continuous Virtual Multi-Agent Systems) by Günter Bruns, Peter Mössinger, Daniel Polani, René Spalt, Thomas Uthmann and Stefan Weber.
Listed below are applications of individual-based models, arranged by general topic area.
Ecology and Biology:
Mixed ecosystems
ATLSS Across Trophic Level System Simulation for the Everglades/Big Cypress Region of South Florida, a very large-scale ecological simulation effort lead by Donald DeAngelis and a cast of thousands. See the related paper: Computational Models of White-Tailed Deer in the Florida Everglades, and this report from Science Alliance News.
Facilitating Mobile Objects within the Context of Simulated Landscape Processes by James D. Westervelt and Lewis D. Hopkins this 1996 paper describes modeling carnivore and herbivore populations as they interact with vegetation in the context of a landscape described with a geographic information system.
Evolution and Spatial Structure Interact to Influence Plant-Herbivore Population and Community Dynamics by Gregg Hartvigsen and Simon Levin. An individual-based model of plant-herbivore interactions and coevolution.
Insect/Plant Interactions Program by Peter Room, Jim Hanan, et al., models growth of individual plants, either singly or in small stands, and interactions with individual insects as they crawl on or fly between the virtual plants.
A Multimodeling Basis for Across-Trophic-Level Ecosystem Modeling: The Florida Everglades Example (1997) by Paul Fishwick, James Sanderson and Wilfried Wolff.
The implementation and visualisation of a large spatial individual-based model using fortran 90 (1996) by Tim Hopkins and David R. Morse. A simulation of the spread of Barley Yellow Dwarf Virus in a barley field, the model considers explicitly each individual plant and aphid.
Fish
Development of a spatially explicit, individual-based model of marine fish early life history by Sarah Hinckley, Albert J. Hermann, and Bernard Megrey, published in Marine Ecology Progress Series. See also Individual-based modeling of walleye pollock in the southeast Bering Sea. And see Ocean Current Model Shows Where Larvae Drift in the ARSC newsletter. See also animation links on A Biophysical Model of Shelikof Strait.
Individual-Based Fish Population Model Applied to Management Issues (1991) Deangelis et al., individual-based population model for smallmouth bass, used to investigate the impact of varying the opening date of the fishing season.
The EPRI CompMech Program: Compensatory Mechanisms in fish populations (at the Electric Power Research Institute, of the Environmental Sciences Division at Oak Ridge National Laboratory). See the software directories containing individual-based models of chinook and trout.
Individual-Based Approach to Analyzing PIT-Tag Data (1997) modeling of migrating salmon based on data from passive transponder (PIT) tags. Contractor technical contact: Kenneth A. Rose
Individual-Based Fish Modeling in the Mathematical Modeling Program at Humboldt State University by Roland Lamberson with Steve Railsback and Steve Jackson
NerkaSim by James Scandol et al. uses individual based models of the migration of salmon. See this snapshot of a simulation run.
Development of an Individual-Based Trout Instream Flow Model (1999) by Russell B. Rader and N. LeRoy Poff
Mammals
Gorilla Simulation work by Mark Scahill including this update and a draft paper called Modeling Mountain Gorillas from around 1995.
Spatially Explicit Population Dynamics and the Snowshoe Hare by Jason A. Thomas. See also his list of links on Spatially-Explicit Population Modelling and Spatial Ecology Modelling and Analysis Software.
Model of Animal Behavior (MOAB) a description of software for a spatially explicit, individual based model of animal movement and foraging behavior by Jacoby Carter and colleagues at the U.S. Geological Survey. See also this poster paper (with illustrations): MOAB: A Spatially-Explicit, Individual Based, Expert System for Creating Animal Foraging Models
PUMA software by Paul Beier was developed to predict the risk of extinction in cougar populations under various development scenarios. The model is individually-based but not spatially explicit
Deer Management Simulator by Ken Risenhoover (et al.?) is a spatially explicit modeling environment for evaluating deer management strategies. See also these summaries of related research at the same lab.
Aggregation and the Emergence of Social Behavior in Rat Pups Modeled by Simple Rules of Individual Behavior (1998) by Jeff Schank (see also) and Jeffrey Alberts models huddling in infant Norway rats.
Birds
The Weaver Project by Matt Hare, Alan Sibbald, and Alistair Law, is a spatially explicit, individual-based model of the red grouse in Scotland's heather moorland. It seeks to provide wildlife managers with advice on appropriate strategies to restore grouse populations.
Multiscale Dynamic Simulation for Ecological Modeling by Pedro Pereira Gonçalves and Maria Paula Antunes studies environmental spatial heterogeneity and the reactions of individual organisms. The system is integrated with a Geographical Information System package enabling the interactions of virtual objects with real data. Includes a model of flocking birds.
Channel Island bald eagle and peregrine falcon populations (1994?) by Gordie Swartzman
Development of a spatially-explicit, individual-based model to simulate Kirtland's Warbler population dynamics (1998) by Carol Bocetti et al. at USGS PWRC.
Insects
Multi-Agent Simulation of Honey Bee Colonies by David Sumpter uses a Swarm-based model to investigate colony activities (particularly thermoregulation) by simulating bee behavior.
Manta by Alexis Drogoul is an ethological simulation of ant colony behavior modeled at the level of individual ants. Several related papers are available online. See also this review of Manta by Howard Gutowitz.
The non-linear dynamics of survival and social facilitation in termites by Octavio Miramontes and Og DeSouza. Uses a "mobile cellular automata" (a mobile, spatially explicit individual-based model in discrete space) to simulate a colony of termites. See also Miramontes' Complexity and Social Behaviour.
An Individual Tree Based Model of Mountain Pine Beetle Invasion (1999) by Emily Stone
Carl Anderson uses agent-based models to study the organisation of workers and work in insect societies and related regulatory mechanisms, particularly task partitioning and self organization in ant and bee colonies. Some papers are avaialble at his older web site.
Forests
Scaling from Trees to Forests: Analysis of a Complex Simulation Model by Doug Deutschman, Simon Levin, Catherine Devine and Linda Buttel. (A very nicely produced multimedia presentation in Science Online.) Spatially explicit forest growth models using SORTIE, a stochastic individual-based simulation model of forest dynamics in which trees compete for light. (See also these SORTIE forest images.)
Arborgames by Melissa Savage and Manor Askenazi examines the role of forest fire on species diversity. Local interaction of trees in a neighborhood allows the model to generate complex landscape dynamics. Bruce Sawhill is collaborating on analysis of model results. Robert Bell is working on a application in Yellowstone.
SmartForest An interactive forest visualizer, by UIUC's Imaging Systems Laboratory, models forest management issues at the level of the individual trees. The software is available for download.
Marine Invertebrates
Ship Fouling by Yosef Cohen. A Java applet demonstrating the interaction of barnacles settling on the hull of a ship and limpets, used as a biological control, which can bulldoze away young barnacles.
A virtual mesocosm with artificial salps for exploring the conditions of swarm development in the pelagic tunicate Salpa fusiformis (1997) Philippe Laval in Marine Ecology Progress Series Volume 154
Arachnids
Mites IBM applet by Nils Kösters at the German Life Sciences Information service. Simulation of the life and times of a breeding population of mites. See also this other copy (?) and this 3D version.
Bacteria
BacSim, a simulator for individual-based modelling of bacterial colony growth (1998) by Jan-Ulrich Kreft, Ginger Booth and Julian Wimpenny. BacSim is based on Gecko, which is based in turn on Swarm
Non-species-specific models, and other topics
The Tragedy of the Commons Java applets and commentary by Walter Korman (from the now defunct weekly column Deep Magic). Based on Garrett Hardin's 1968 paper.
Parallel Software Tools for Ecological Simulation including the Java-based GUST which runs an interactive version of their Szymanski-Caraco cellular automata model. See their Guide to Related Research.
Ecomachines and Spatial Modeling in Ecology and Biology was a workshop held January 13-16, 1996 at the Santa Fe Institute.
Gecko, a spatial individual-based simulator for modeling ecosystem dynamics, by Oswald Schmitz and Ginger Booth.
ECOTOOLS uses individual-based models to study animal behavior and ecological issues. See descriptions of various ECOSIM reimplemented models: schooling, flocking, storks, dragonflies, crowns, largemouth bass, northern cod.
Theoretical Ecology of Spatial Heterogeneity: An IBM Approach ongoing work by Kim Cuddington on "...the effects of limited mobility and spatial structure or heterogeneity on the population dynamics and stability of communities." See also these resources on theoretical ecology.
Methods, Conceptions & Ideas on Ecological Modelling by Andrey Tsyplianovsky. This extensive site covers many aspects of ecological modeling and includes a comprehensive list of links on individual-based models.
Ten years of individual-based modelling in ecology: what have we learned, and what could we learn in the future? (1999) by Volker Grimm in a special issue of Ecological Modelling on Individual-based models.
Forager, from Amber Waves Software, simulates foraging (feeding behavior). Users can set up animal behavior models, graphically design the foraging environment and specify behavior rules.
Papers from the Third International Conference/Workshop on Integrating GIS and Environmental Modeling January 21-25, 1996, Santa Fe, New Mexico:
Individual-Based Models in Ecology: An Overview by Donald L. DeAngelis, D. M. Fleming, L. J. Gross, and W. F. Wolff,
Some Guidelines For Implementing Spatially Explicit, Individual-Based Ecological Models Within Location-Based Raster GIS. by Roger L. Slothower, Paul A. Schwarz, and Kevin M. Johnston
Spatial Modeling of Aquatic Habitat From a Fish's Perspective by John K. Horne, J. Michael Jech, and Stephen B. Brandt
From Individuals to Populations, papers from a 1998 International Workshop and Young Scientists School held in Ceske Budejovice, Czech Republic:
On individual-based models for single-species population growth, predator-prey interaction and optimal foraging
Individual behaviour and population dynamics: a protocol for extracting population growth rates from individual-based models
An individual-based model of mite predator-prey populations: local dynamics
From individuals to population in parasitoid-host and predator-prey models
Biola: a new biological programming language for developing individual based models
Instructional Tools:
EcoBeaker by Eli Meir is an ecological simulation program, designed for use by students in the classroom.
The Virtual Forest by EcoLogik and BeakerWare
Individual-based ecological models: Spatial models for undergraduate investigation by Louis J. Gross
Modeling Humans (and Artificial Societies)
Human Crowds: motion and psychology
An Agent Based Simulation Environment for Public Order Management Training by Roderick Williams is a tool to help train training police officers to manage large public gatherings (crowds, demonstrations, marches). See also the page for the CACTUS (Command And Control Training and Planning Using Knowledge Based Simulation) system.
Legion by G. Keith Still is used to simulate the motion of large crowds of people. It can handle crowds of more than 100,000 people.
Animation Science Corporation sells tools to model the motion of large crowds with their Rampage software, based on an efficient engine for interacting particle systems.
EINSTein (Enhanced ISAAC Neural Simulation Toolkit), an artificial-life laboratory for exploring self-organized emergent behavior in land combat, by Andy Ilachinski of the (US) Center For Naval Analyses.
The Collective Action Project by Clark McPhail and John McCarthy, studies individual and collective actions of people in large temporary gatherings (crowds, mobs, demonstrations). See also A Computer Simulation of a Sociological Experiment (1995) by David Schweingruber based on the GATHERING simulation written by William T. Powers, based on Perception Control Theory.
An Agent-Based Model of Seating In A Theater a Java-based class project by Yale Wang. See also his version of Schelling's Segregation Model and the El Farol problem: how the appropriate number of people decide to show up for an event.
Modeling Audience Group Behavior by Nuria Oliver and Stephen Intille describes an agent based model (spatially explicit, discrete space, non-mobile) of synchronization and other decentralized collaborative behaviors of a group audience.
Anthropology
Swarm-based Modeling of Prehistoric Settlement Systems in Southwestern North America (1997) by Tim Kohler and Eric Carr, describes an agent-based simulation constructed with the Swarm system. See also this 1995 paper: Agent-Based Modeling of Anasazi Village Formation in the Northern American Southwest.
Computational Anthropology: The Simulation and Representation of Bio-Cultural Processes, a section of the American Anthropological Association.
The Cultural Transmission Project studies population structure, cultural transmission, and evolutionary theory. Some of its research involves individual-based models, such as the use of Swarm in Building Expectations for "Wasteful" Behavior among Human Populations.
Culture Group Meeting: Agent-Based Modeling of Small-Scale Societies report on summer 1998 meeting at SFI.
Artificial Societies
Sugarscape (and the book Growing Artificial Societies: Social Science From the Bottom Up) by Joshua M. Epstein and Robert Axtell. Describes experiments with an artificial society, a computer model consisting of a population of autonomous agents and a separate environment in which the agents live. See also this Discovery Online feature and this Science News article.
Artificial Societies and Psychological Agents (abstract, 1996) by Stuart Watt (see also the full paper in PDF format) towards the development of "psychological agents" better suited for interaction with humans.
Sociology
Simulation: a emergent perspective, text of a lecture advocating use of individual-based models in sociology and related fields, by Nigel Gilbert. See related material at The Computer Simulation of Societies site.
Agency and Interaction (PDF 171K) by Peter J. Burke considers the connection between macro-level group characteristics (social structure) and the micro-level interaction between individuals.
Interpersonal Communication
Coordinating Turn-Taking with Gaze by David G. Novick, Brian Hansen and Karen Ward. Uses an individual-based model to validate the proposed mechanism.
Formal Approaches to Innate and Learned Communication: Laying the Foundation for Language (1997) by Mike Oliphant. Identifies the conditions necessary to establish a system of communication in a population of individuals, whether through evolution or learning.
Emotion
New Fungus Eater Experiments by Thomas Wehrle describes a multi-agent framework for investigation of the psychology of emotion, based on a model proposed by Masanao Toda.
Emotional Intelligence in Multi-Agent Simulation (1998) by Eric Werk, on designing believable agents.
other topics
Theory in a Complex World: Computational Laboratories in Economic Geography by Catherine Dibble explores the gap between simulation experiments and a understanding of the underlying phenomena.
Spatially-Explicit Autonomous Agents for Modelling Recreation Use in Complex Wilderness Landscapes by Randy Gimblett, Bohdan Durnota and Bob Itami, uses autonomous agents to assist natural resource managers in assessing and managing dynamic recreation behavior, social interactions and resulting conflicts in wilderness settings. See also the Recreation Behavior Simulator (RBSim) which simulates the behavior of human recreators in high use natural environments.
Rational Actors Versus Adaptive Agents: Social Science Implications (1998) by Paul E. Johnson. A comparison of two research methods, "rational choice theory" and "agent-based modeling." Is agent-based modeling really different and is it really better? Johnson says the answers are "yes" and "sometimes"... Uses SWARM. (Figures are here.)
CORSIM is a microsimulation model of individual and family behavior through time. See the paper Dynamic Microsimulation and the CORSIM 3.0 Model (1993) by Steven B. Caldwell, and this list of current research projects.
The Uses of Sim Sidewalks an essay by Steven Johnson in FEED Magazine: "What happens when urban scholars sit down to play SimCity?"
Economics
Playing the game of life by Rita Koselka (an April 7, 1997 article from Forbes) covers individual-based models of the music CD business by the Emergent Solutions Group of PricewaterhouseCoopers, the stock market by W. Brian Arthur and John Holland, the Sugarscape model by Joshua Epstein and Robert Axtell, and Challenge from Thinking Tools.
Aspen, a microanalytic model to simulate the U.S. economy. Aspen uses economic agents to represent the various decision-making segments, and the microanalytic simulation process models each agent individually. See also this earlier press briefing.
Agent-Based Computational Economics (ACE) by Leigh Tesfatsion, a computational study of economies modeled as evolving decentralized systems of autonomous interacting agents. Which seeks to explain these global regularities in economic processes from the bottom up. See also How Economists Can Get Alife: Abbreviated Version
Agent based simulation of artificial electricity markets by Raimo P. Hämäläinen et al. models how customers respond to different price patterns for electrical power.
Artificial Life Simulation of the Textile/Apparel Marketplace: An Innovative Approach to Strategizing about Evolving Markets by Evelyn L. Brannon, Lenda Jo Anderson, R. Alan Donaldson, Thomas E. Marshall, Pamela V. Ulrich.
Economic Modeling of Global Innovation Diffusion, Diploma Thesis of Johannes Kottonau and Friedemann Buergel (aka Bürgel) uses an agent based simulation model called LEM 1.1 to visualize cultural, institutional, economic and legal key factors of spacio-temporal diffusion of new technologies (specifically Light Electric Vehicles (LEVs)).
Agent Based Simulation of the Hotelling Game by Michael Friedlander and David Sumpter a spatial variation on a model of the pricing of identical goods by the only two shops in a town.
Market Organisation by Gerard Weisbuch , Alan Kirman and Dorothea Herreiner, also available as SFI working paper 95-11-102.
Traffic and vehicle simulations
Hank is an interactive automotive driving simulation with an individual-based model of autonomous vehicle traffic and pedestrians. These provide the dynamic environment and allow authoring scenarios. By Jim Cremer, Joe Kearney and the Hank Team.
MITSIM A Microscopic Traffic Simulator for Evaluation of Dynamic Traffic Management Systems developed at MIT's Intelligent Transportation Systems lab by Qi Yang and Haris N. Koutsopoulos
Microsimulation of road traffic a very nice Java applet demonstrating a continuous "microscopic" model of traffic dynamics in several scenarios by Martin Treiber and Dirk Helbing. See also Discrete Force Model for Pedestrian Motion Java applets by Kai Bolay and Dirk Helbing.
Stop-and-Go Science (1999) by Peter Weiss in Science News Online. Survey article: "by better understanding traffic flow, researchers hope to keep down highway congestion."
Transportation Analysis and Simulation System at the Los Alamos National Laboratory. "TRANSIMS models a metropolitan region with a representation of the inhabitants, their activities, and the transportation infrastructure. TRANSIMS then simulates the movement of individuals across the transportation network, including their use of vehicles such as cars or buses, on a second-by-second basis."
Smartest Project (Simulation Modelling Applied to Road Transport European Scheme Tests) by Ken Fox. See also these lists of traffic micro-simulation links and abstracts.
The STEER Traffic Simulator (Signals/Traffic Emulator with Event-based Responsiveness) is a program intended to simulate traffic on an urban network, modeling up to tens of thousands of vehicles.
METROPOLIS 1.0 is a modular system for Dynamic Traffic Simulations: It is aimed towards on-line as well as off-line simulations of traffic flows in an urban context and for large networks.
SmartPath simulation and animation package for traffic studies. See also Smart AHS a specification, simulation and evaluation framework for modeling, control and evaluation of Automated Highway Systems (AHS). Both part of California's PATH (Partners for Advances Transit and Highways)
Demonstration of Traf-Netsim for Traffice Operations Management: Final Report (1991) by Joan D. Sulzberg and Michael J. Demetsky. A "microscopic level" simulation of cars, buses and pedestrians.
Elevator Demos an individual-based simlulation model of a set of elevators in a ten story building. Uses a Java applet graphical front-end and a MODSIM III back-end running on a remote server.
Animation and Interactive Multimedia
The boids model of coordinated group motion such as flocks, herds and schools by Craig Reynolds. See also these demos of other related steering behaviors.
Artificial Animals for Computer Animation: Biomechanics, Locomotion, Perception, and Behavior (Ph.D Dissertation, 1996) by Xiaoyuan Tu. A biologically plausible, physically based model of fish ethology at the individual level.
The Virtual Fishtank is an interactive museum exhibit developed (by The Computer Museum, MIT Media Lab, and NearLife Inc.) to introduce visitors to the phenomena of emergence and ideas from the sciences of complexity. See also these pages about The Virtual Fishtank at MIT and NearLife.
Related topics
Stochastic Spatial Models: A Hyper-Tutorial by Rick Durrett covers stochastic spatial models and their applications to biology.
Annotated list of links related to metapopulation biology, spatial population biology, landscape ecology by Dag Hjermann
Distributed Modular Spatial Ecosystem Modeling by Thomas Maxwell and Robert Costanza of the International Institute for Ecological Economics, and see the related Spatio-Temporal Modeling Page
WWW-Server for Ecological Modeling at the University of Kassel
A Multiple-Mechanism Developmental Model for Defining Self-Organizing Geometric Structures (1995) by Kurt Fleischer simulates the self-organization of structures in space at the level of individual "cells". See some images from this work.
MOSAIC: Simulation Modeling and Analysis of Cellular Interactions (warning, that is a traslation of the subtitle by a non-French-speaking American (me)).
Internet Ecologies Area at Xerox Palo Alto Research Center
Multi-robot systems:
Many-Robot Systems a US Navy site with a collection of papers about systems involving multiple robots. Explores collective action, cooperation, communication and self-organization.
Intelligent Methods for Multi-Agent Environments (1997) by Cem Ünsal. Presentation on self-organization and cooperation in natural and robotic groups.
Self-Organization in Large Populations of Mobile Robots (1993) by Cem Ünsal. Describes the use of a homogeneous population of robots, an Army-ant swarm, for transportation of material.
The Ants: A Community of Microrobots and their social behavior
The Amorphous Computing group at MIT explores issues such as "How do we obtain coherent behavior from the cooperation of large numbers of unreliable parts that are interconnected in unknown, irregular, and time-varying ways?"
Co-ordination in Artificial Agent Societies Social Structures and Its Implications for Autonomous Problem-Solving Agents (1999) by Sascha Ossowski
Microsimulation links at CRESS Centre for Research on Simulation in the Social Sciences
Mirror Worlds: Or the Day Software Puts the Universe in a Shoebox...How It Will Happen and What It Will Mean (1991) by David Gelernter. See also this bio of Gelernter and this review of Mirror Worlds in CTHEORY.
Web-Based Simulation links by Paul Fishwick, and A Survey of Web-Based Simulation by Ernie Page
Offline resources
Books
Individual-Based Models and Approaches in Ecology: Populations, Communities and Ecosystems, by Donald L. Deangelis, Louis J. Gross (Editors), published in 1992 by Chapman and Hall.
The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration by Robert Axelrod, published in 1997 by Princeton University Press. See also this online supplement.
Simulating Organizations: Computational Models of Institutions and Groups (1998) edited by Michael Prietula, Kathleen Carley and Les Gasser.
Turtles, Termites, and Traffic Jams Explorations in Massively Parallel Microworlds (1997) by Mitchel Resnick
How Hits Happen--Forecasting Predictability in a Chaotic Marketplace (1998) by Winslow Farrell, with foreword by Brian Arthur. Using agent-based models to simulate the consumers of pop culture. Find it at Amazon.com or ACSES.
Laboratories and Groups
Academic
Dynamic Landscape Simulation Modeling group of the Geographic Modeling Systems Laboratory at UIUC. See the page on Dynamic, Spatial, Ecological Modeling with links to spatially explicit models related to birds at Fort Hood, the desert tortoise, and a quasi-individual-based model of the sage grouse.
ECOTOOLS (and WESP) at the University of Oldenburg, develop tools to support the modeling and simulation of individual-oriented ecological models.
Wildlife Habitat Analysis Lab of the Department of Wildlife & Fisheries Sciences at Texas A&M University. See these Research Summaries.
Center for Computable Economics at University of California, Los Angeles. See for example Agent Based Simulations as a tool in Economics.
The Sony Computer Science Laboratory Paris has a research project on evolutionary linguistics which make use of indivudual-based models to study the emergence of language and meaning.
Project for the Simulation of Social Behaviour within the Italian National Research Council - Institute of Psychology. Within this program, formal models of interactions among intelligent autonomous agents have been developed and some computer simulation studies have been conducted.
Centre for Policy Modelling at Manchester Metropolitan University, especially the Special Interest Group on Agent Based Social Simulation.
Commercial
The Emergent Systems Group of PricewaterhouseCoopers uses multiple agent systems to model decision making and trends in various simulations of real world marketplaces. See Flight Simulators for Management (BusinessWeek 1998: "computer models may give execs previews of how decisions pan out") and Playing the game of life (Forbes 1997).
Thinking Tools uses Agent Based Adaptive Simulation technology to create the management equivalent of flight simulators to help train business decision-makers on a risk-free "practice field". An early project was TeleSim.
Journals
Journal of Artifical Societies and Social Simulation (JASSS)
Conferences
Past
Economic Simulation Conference Conference Proceedings February 9-10, 1996.
From Animals To Animats (SAB98) Fifth International Conference of the Society for Adaptive Behavior, University of Zurich, August 17-21 1998, Zurich, Switzerland.
Sixth International Conference on Artificial Life (Alife VI) June 27-29, 1998, University of California, Los Angeles, USA.
Multi-Agent Systems and Agent-Based Simulation (MABS 98) one of the eight meetings (including Third International Conference on Multi-Agent Systems (ICMAS 98)) comprising Agents' World
First International Conference on Virtual Worlds, July 1-3, 1998, International Institute of Multimedia, Paris, France.
Local Interaction and Global Phenomena in Vegetation and Other Systems, April 19-23, 1999, Institute for Mathematics and its Applications, University of Minnesota
Future
Workshop on Traffic and Granular Flow '99, September 27-29, 1999, University of Stuttgart, Germany.
an annotated list of links
by Craig Reynolds
Individual-based models are simulations based on the global consequences of local interactions of members of a population. These individuals might represent plants and animals in ecosystems, vehicles in traffic, people in crowds, or autonomous characters in animation and games. These models typically consist of an environment or framework in which the interactions occur and some number of individuals defined in terms of their behaviors (procedural rules) and characteristic parameters. In an individual-based model, the characteristics of each individual are tracked through time. This stands in contrast to modeling techniques where the characteristics of the population are averaged together and the model attempts to simulate changes in these averaged characteristics for the whole population. Individual-based models are also known as entity or agent based models, and as individual/entity/agent-based simulations.
Some individual-based models are also spatially explicit meaning that the individuals are associated with a location in geometrical space. Some spatially explicit individual-based models also exhibit mobility, where the individuals can move around their environment. This would be a natural model, for example, of an animal in an ecological simulation. Whereas plants in the same simulation would not be mobile. Some individual-based models are not spatially explicit, for example a simulation of a computer network might be based on individual models of the networked computers, but their location would be irrelevant. Spatially explicit models may use either continuous (real valued) or discrete (integer valued, grid-like) space.
Individual-based models are a subset of multi-agent systems which includes any computational system whose design is fundamentally composed of a collection of interacting parts. For example an "expert system" might be composed of many distinct bits of advice which interact to produce a solution. Individual-based models are distinguished by the fact that each "agent" corresponds to autonomous individual in the simulated domain.
There is an overlap between individual-based models and cellular automata. Certainly cellular automata are similar to spatially-explicit, grid-based, immobile individual-based models. However CAs are always homogeneous and dense (all cells are identical), whereas a grid-based individual-based model might occupy only a few grid cells, and more than one distinct type of individual might live on the same grid. (Of course a CA can have cells in various states, and so represent concepts like empty or occupied by type 3. Perhaps the significant difference is whether the simulation's inner loop proceeds cell by cell, or individual by individual. (Although that distinction is muddied by parallel-processing hardware.)) The philosophical issue is whether the simulation is based on a dense and uniform dissection of the space (as in a CA), or based on specific individuals distributed within the space.
Of course, note that everyone uses terminology differently, so take the definitions above with a grain of salt. ("Your mileage may differ.")
My interest in this area began when I made a model of bird flocks and related group motion. As a result I am particularly interested in individual-based models using spatially explicit mobile agents in continuous space. This bias may be reflected in the selection of resources listed below.
Online resources
These are general purpose software toolkits useful for implementing individual-based models.
Swarm is a software package for multi-agent simulation of complex systems originally developed at The Santa Fe Institute and now at the Swarm Development Group (SDG). See this preliminary version of the Swarm FAQ and these example applications built using the Swarm system.
Echo, conceived by John Holland, is a ecology simulation framework, whose individuals live in a discrete spatially-explicit world and evolve according to a genetic algorithm. See Modelling Complex Adaptive Systems with Echo (1995) by Terry Jones and Stephanie Forrest
XRaptor (A Simulation Environment for Continuous Virtual Multi-Agent Systems) by Günter Bruns, Peter Mössinger, Daniel Polani, René Spalt, Thomas Uthmann and Stefan Weber.
Listed below are applications of individual-based models, arranged by general topic area.
Ecology and Biology:
Mixed ecosystems
ATLSS Across Trophic Level System Simulation for the Everglades/Big Cypress Region of South Florida, a very large-scale ecological simulation effort lead by Donald DeAngelis and a cast of thousands. See the related paper: Computational Models of White-Tailed Deer in the Florida Everglades, and this report from Science Alliance News.
Facilitating Mobile Objects within the Context of Simulated Landscape Processes by James D. Westervelt and Lewis D. Hopkins this 1996 paper describes modeling carnivore and herbivore populations as they interact with vegetation in the context of a landscape described with a geographic information system.
Evolution and Spatial Structure Interact to Influence Plant-Herbivore Population and Community Dynamics by Gregg Hartvigsen and Simon Levin. An individual-based model of plant-herbivore interactions and coevolution.
Insect/Plant Interactions Program by Peter Room, Jim Hanan, et al., models growth of individual plants, either singly or in small stands, and interactions with individual insects as they crawl on or fly between the virtual plants.
A Multimodeling Basis for Across-Trophic-Level Ecosystem Modeling: The Florida Everglades Example (1997) by Paul Fishwick, James Sanderson and Wilfried Wolff.
The implementation and visualisation of a large spatial individual-based model using fortran 90 (1996) by Tim Hopkins and David R. Morse. A simulation of the spread of Barley Yellow Dwarf Virus in a barley field, the model considers explicitly each individual plant and aphid.
Fish
Development of a spatially explicit, individual-based model of marine fish early life history by Sarah Hinckley, Albert J. Hermann, and Bernard Megrey, published in Marine Ecology Progress Series. See also Individual-based modeling of walleye pollock in the southeast Bering Sea. And see Ocean Current Model Shows Where Larvae Drift in the ARSC newsletter. See also animation links on A Biophysical Model of Shelikof Strait.
Individual-Based Fish Population Model Applied to Management Issues (1991) Deangelis et al., individual-based population model for smallmouth bass, used to investigate the impact of varying the opening date of the fishing season.
The EPRI CompMech Program: Compensatory Mechanisms in fish populations (at the Electric Power Research Institute, of the Environmental Sciences Division at Oak Ridge National Laboratory). See the software directories containing individual-based models of chinook and trout.
Individual-Based Approach to Analyzing PIT-Tag Data (1997) modeling of migrating salmon based on data from passive transponder (PIT) tags. Contractor technical contact: Kenneth A. Rose
Individual-Based Fish Modeling in the Mathematical Modeling Program at Humboldt State University by Roland Lamberson with Steve Railsback and Steve Jackson
NerkaSim by James Scandol et al. uses individual based models of the migration of salmon. See this snapshot of a simulation run.
Development of an Individual-Based Trout Instream Flow Model (1999) by Russell B. Rader and N. LeRoy Poff
Mammals
Gorilla Simulation work by Mark Scahill including this update and a draft paper called Modeling Mountain Gorillas from around 1995.
Spatially Explicit Population Dynamics and the Snowshoe Hare by Jason A. Thomas. See also his list of links on Spatially-Explicit Population Modelling and Spatial Ecology Modelling and Analysis Software.
Model of Animal Behavior (MOAB) a description of software for a spatially explicit, individual based model of animal movement and foraging behavior by Jacoby Carter and colleagues at the U.S. Geological Survey. See also this poster paper (with illustrations): MOAB: A Spatially-Explicit, Individual Based, Expert System for Creating Animal Foraging Models
PUMA software by Paul Beier was developed to predict the risk of extinction in cougar populations under various development scenarios. The model is individually-based but not spatially explicit
Deer Management Simulator by Ken Risenhoover (et al.?) is a spatially explicit modeling environment for evaluating deer management strategies. See also these summaries of related research at the same lab.
Aggregation and the Emergence of Social Behavior in Rat Pups Modeled by Simple Rules of Individual Behavior (1998) by Jeff Schank (see also) and Jeffrey Alberts models huddling in infant Norway rats.
Birds
The Weaver Project by Matt Hare, Alan Sibbald, and Alistair Law, is a spatially explicit, individual-based model of the red grouse in Scotland's heather moorland. It seeks to provide wildlife managers with advice on appropriate strategies to restore grouse populations.
Multiscale Dynamic Simulation for Ecological Modeling by Pedro Pereira Gonçalves and Maria Paula Antunes studies environmental spatial heterogeneity and the reactions of individual organisms. The system is integrated with a Geographical Information System package enabling the interactions of virtual objects with real data. Includes a model of flocking birds.
Channel Island bald eagle and peregrine falcon populations (1994?) by Gordie Swartzman
Development of a spatially-explicit, individual-based model to simulate Kirtland's Warbler population dynamics (1998) by Carol Bocetti et al. at USGS PWRC.
Insects
Multi-Agent Simulation of Honey Bee Colonies by David Sumpter uses a Swarm-based model to investigate colony activities (particularly thermoregulation) by simulating bee behavior.
Manta by Alexis Drogoul is an ethological simulation of ant colony behavior modeled at the level of individual ants. Several related papers are available online. See also this review of Manta by Howard Gutowitz.
The non-linear dynamics of survival and social facilitation in termites by Octavio Miramontes and Og DeSouza. Uses a "mobile cellular automata" (a mobile, spatially explicit individual-based model in discrete space) to simulate a colony of termites. See also Miramontes' Complexity and Social Behaviour.
An Individual Tree Based Model of Mountain Pine Beetle Invasion (1999) by Emily Stone
Carl Anderson uses agent-based models to study the organisation of workers and work in insect societies and related regulatory mechanisms, particularly task partitioning and self organization in ant and bee colonies. Some papers are avaialble at his older web site.
Forests
Scaling from Trees to Forests: Analysis of a Complex Simulation Model by Doug Deutschman, Simon Levin, Catherine Devine and Linda Buttel. (A very nicely produced multimedia presentation in Science Online.) Spatially explicit forest growth models using SORTIE, a stochastic individual-based simulation model of forest dynamics in which trees compete for light. (See also these SORTIE forest images.)
Arborgames by Melissa Savage and Manor Askenazi examines the role of forest fire on species diversity. Local interaction of trees in a neighborhood allows the model to generate complex landscape dynamics. Bruce Sawhill is collaborating on analysis of model results. Robert Bell is working on a application in Yellowstone.
SmartForest An interactive forest visualizer, by UIUC's Imaging Systems Laboratory, models forest management issues at the level of the individual trees. The software is available for download.
Marine Invertebrates
Ship Fouling by Yosef Cohen. A Java applet demonstrating the interaction of barnacles settling on the hull of a ship and limpets, used as a biological control, which can bulldoze away young barnacles.
A virtual mesocosm with artificial salps for exploring the conditions of swarm development in the pelagic tunicate Salpa fusiformis (1997) Philippe Laval in Marine Ecology Progress Series Volume 154
Arachnids
Mites IBM applet by Nils Kösters at the German Life Sciences Information service. Simulation of the life and times of a breeding population of mites. See also this other copy (?) and this 3D version.
Bacteria
BacSim, a simulator for individual-based modelling of bacterial colony growth (1998) by Jan-Ulrich Kreft, Ginger Booth and Julian Wimpenny. BacSim is based on Gecko, which is based in turn on Swarm
Non-species-specific models, and other topics
The Tragedy of the Commons Java applets and commentary by Walter Korman (from the now defunct weekly column Deep Magic). Based on Garrett Hardin's 1968 paper.
Parallel Software Tools for Ecological Simulation including the Java-based GUST which runs an interactive version of their Szymanski-Caraco cellular automata model. See their Guide to Related Research.
Ecomachines and Spatial Modeling in Ecology and Biology was a workshop held January 13-16, 1996 at the Santa Fe Institute.
Gecko, a spatial individual-based simulator for modeling ecosystem dynamics, by Oswald Schmitz and Ginger Booth.
ECOTOOLS uses individual-based models to study animal behavior and ecological issues. See descriptions of various ECOSIM reimplemented models: schooling, flocking, storks, dragonflies, crowns, largemouth bass, northern cod.
Theoretical Ecology of Spatial Heterogeneity: An IBM Approach ongoing work by Kim Cuddington on "...the effects of limited mobility and spatial structure or heterogeneity on the population dynamics and stability of communities." See also these resources on theoretical ecology.
Methods, Conceptions & Ideas on Ecological Modelling by Andrey Tsyplianovsky. This extensive site covers many aspects of ecological modeling and includes a comprehensive list of links on individual-based models.
Ten years of individual-based modelling in ecology: what have we learned, and what could we learn in the future? (1999) by Volker Grimm in a special issue of Ecological Modelling on Individual-based models.
Forager, from Amber Waves Software, simulates foraging (feeding behavior). Users can set up animal behavior models, graphically design the foraging environment and specify behavior rules.
Papers from the Third International Conference/Workshop on Integrating GIS and Environmental Modeling January 21-25, 1996, Santa Fe, New Mexico:
Individual-Based Models in Ecology: An Overview by Donald L. DeAngelis, D. M. Fleming, L. J. Gross, and W. F. Wolff,
Some Guidelines For Implementing Spatially Explicit, Individual-Based Ecological Models Within Location-Based Raster GIS. by Roger L. Slothower, Paul A. Schwarz, and Kevin M. Johnston
Spatial Modeling of Aquatic Habitat From a Fish's Perspective by John K. Horne, J. Michael Jech, and Stephen B. Brandt
From Individuals to Populations, papers from a 1998 International Workshop and Young Scientists School held in Ceske Budejovice, Czech Republic:
On individual-based models for single-species population growth, predator-prey interaction and optimal foraging
Individual behaviour and population dynamics: a protocol for extracting population growth rates from individual-based models
An individual-based model of mite predator-prey populations: local dynamics
From individuals to population in parasitoid-host and predator-prey models
Biola: a new biological programming language for developing individual based models
Instructional Tools:
EcoBeaker by Eli Meir is an ecological simulation program, designed for use by students in the classroom.
The Virtual Forest by EcoLogik and BeakerWare
Individual-based ecological models: Spatial models for undergraduate investigation by Louis J. Gross
Modeling Humans (and Artificial Societies)
Human Crowds: motion and psychology
An Agent Based Simulation Environment for Public Order Management Training by Roderick Williams is a tool to help train training police officers to manage large public gatherings (crowds, demonstrations, marches). See also the page for the CACTUS (Command And Control Training and Planning Using Knowledge Based Simulation) system.
Legion by G. Keith Still is used to simulate the motion of large crowds of people. It can handle crowds of more than 100,000 people.
Animation Science Corporation sells tools to model the motion of large crowds with their Rampage software, based on an efficient engine for interacting particle systems.
EINSTein (Enhanced ISAAC Neural Simulation Toolkit), an artificial-life laboratory for exploring self-organized emergent behavior in land combat, by Andy Ilachinski of the (US) Center For Naval Analyses.
The Collective Action Project by Clark McPhail and John McCarthy, studies individual and collective actions of people in large temporary gatherings (crowds, mobs, demonstrations). See also A Computer Simulation of a Sociological Experiment (1995) by David Schweingruber based on the GATHERING simulation written by William T. Powers, based on Perception Control Theory.
An Agent-Based Model of Seating In A Theater a Java-based class project by Yale Wang. See also his version of Schelling's Segregation Model and the El Farol problem: how the appropriate number of people decide to show up for an event.
Modeling Audience Group Behavior by Nuria Oliver and Stephen Intille describes an agent based model (spatially explicit, discrete space, non-mobile) of synchronization and other decentralized collaborative behaviors of a group audience.
Anthropology
Swarm-based Modeling of Prehistoric Settlement Systems in Southwestern North America (1997) by Tim Kohler and Eric Carr, describes an agent-based simulation constructed with the Swarm system. See also this 1995 paper: Agent-Based Modeling of Anasazi Village Formation in the Northern American Southwest.
Computational Anthropology: The Simulation and Representation of Bio-Cultural Processes, a section of the American Anthropological Association.
The Cultural Transmission Project studies population structure, cultural transmission, and evolutionary theory. Some of its research involves individual-based models, such as the use of Swarm in Building Expectations for "Wasteful" Behavior among Human Populations.
Culture Group Meeting: Agent-Based Modeling of Small-Scale Societies report on summer 1998 meeting at SFI.
Artificial Societies
Sugarscape (and the book Growing Artificial Societies: Social Science From the Bottom Up) by Joshua M. Epstein and Robert Axtell. Describes experiments with an artificial society, a computer model consisting of a population of autonomous agents and a separate environment in which the agents live. See also this Discovery Online feature and this Science News article.
Artificial Societies and Psychological Agents (abstract, 1996) by Stuart Watt (see also the full paper in PDF format) towards the development of "psychological agents" better suited for interaction with humans.
Sociology
Simulation: a emergent perspective, text of a lecture advocating use of individual-based models in sociology and related fields, by Nigel Gilbert. See related material at The Computer Simulation of Societies site.
Agency and Interaction (PDF 171K) by Peter J. Burke considers the connection between macro-level group characteristics (social structure) and the micro-level interaction between individuals.
Interpersonal Communication
Coordinating Turn-Taking with Gaze by David G. Novick, Brian Hansen and Karen Ward. Uses an individual-based model to validate the proposed mechanism.
Formal Approaches to Innate and Learned Communication: Laying the Foundation for Language (1997) by Mike Oliphant. Identifies the conditions necessary to establish a system of communication in a population of individuals, whether through evolution or learning.
Emotion
New Fungus Eater Experiments by Thomas Wehrle describes a multi-agent framework for investigation of the psychology of emotion, based on a model proposed by Masanao Toda.
Emotional Intelligence in Multi-Agent Simulation (1998) by Eric Werk, on designing believable agents.
other topics
Theory in a Complex World: Computational Laboratories in Economic Geography by Catherine Dibble explores the gap between simulation experiments and a understanding of the underlying phenomena.
Spatially-Explicit Autonomous Agents for Modelling Recreation Use in Complex Wilderness Landscapes by Randy Gimblett, Bohdan Durnota and Bob Itami, uses autonomous agents to assist natural resource managers in assessing and managing dynamic recreation behavior, social interactions and resulting conflicts in wilderness settings. See also the Recreation Behavior Simulator (RBSim) which simulates the behavior of human recreators in high use natural environments.
Rational Actors Versus Adaptive Agents: Social Science Implications (1998) by Paul E. Johnson. A comparison of two research methods, "rational choice theory" and "agent-based modeling." Is agent-based modeling really different and is it really better? Johnson says the answers are "yes" and "sometimes"... Uses SWARM. (Figures are here.)
CORSIM is a microsimulation model of individual and family behavior through time. See the paper Dynamic Microsimulation and the CORSIM 3.0 Model (1993) by Steven B. Caldwell, and this list of current research projects.
The Uses of Sim Sidewalks an essay by Steven Johnson in FEED Magazine: "What happens when urban scholars sit down to play SimCity?"
Economics
Playing the game of life by Rita Koselka (an April 7, 1997 article from Forbes) covers individual-based models of the music CD business by the Emergent Solutions Group of PricewaterhouseCoopers, the stock market by W. Brian Arthur and John Holland, the Sugarscape model by Joshua Epstein and Robert Axtell, and Challenge from Thinking Tools.
Aspen, a microanalytic model to simulate the U.S. economy. Aspen uses economic agents to represent the various decision-making segments, and the microanalytic simulation process models each agent individually. See also this earlier press briefing.
Agent-Based Computational Economics (ACE) by Leigh Tesfatsion, a computational study of economies modeled as evolving decentralized systems of autonomous interacting agents. Which seeks to explain these global regularities in economic processes from the bottom up. See also How Economists Can Get Alife: Abbreviated Version
Agent based simulation of artificial electricity markets by Raimo P. Hämäläinen et al. models how customers respond to different price patterns for electrical power.
Artificial Life Simulation of the Textile/Apparel Marketplace: An Innovative Approach to Strategizing about Evolving Markets by Evelyn L. Brannon, Lenda Jo Anderson, R. Alan Donaldson, Thomas E. Marshall, Pamela V. Ulrich.
Economic Modeling of Global Innovation Diffusion, Diploma Thesis of Johannes Kottonau and Friedemann Buergel (aka Bürgel) uses an agent based simulation model called LEM 1.1 to visualize cultural, institutional, economic and legal key factors of spacio-temporal diffusion of new technologies (specifically Light Electric Vehicles (LEVs)).
Agent Based Simulation of the Hotelling Game by Michael Friedlander and David Sumpter a spatial variation on a model of the pricing of identical goods by the only two shops in a town.
Market Organisation by Gerard Weisbuch , Alan Kirman and Dorothea Herreiner, also available as SFI working paper 95-11-102.
Traffic and vehicle simulations
Hank is an interactive automotive driving simulation with an individual-based model of autonomous vehicle traffic and pedestrians. These provide the dynamic environment and allow authoring scenarios. By Jim Cremer, Joe Kearney and the Hank Team.
MITSIM A Microscopic Traffic Simulator for Evaluation of Dynamic Traffic Management Systems developed at MIT's Intelligent Transportation Systems lab by Qi Yang and Haris N. Koutsopoulos
Microsimulation of road traffic a very nice Java applet demonstrating a continuous "microscopic" model of traffic dynamics in several scenarios by Martin Treiber and Dirk Helbing. See also Discrete Force Model for Pedestrian Motion Java applets by Kai Bolay and Dirk Helbing.
Stop-and-Go Science (1999) by Peter Weiss in Science News Online. Survey article: "by better understanding traffic flow, researchers hope to keep down highway congestion."
Transportation Analysis and Simulation System at the Los Alamos National Laboratory. "TRANSIMS models a metropolitan region with a representation of the inhabitants, their activities, and the transportation infrastructure. TRANSIMS then simulates the movement of individuals across the transportation network, including their use of vehicles such as cars or buses, on a second-by-second basis."
Smartest Project (Simulation Modelling Applied to Road Transport European Scheme Tests) by Ken Fox. See also these lists of traffic micro-simulation links and abstracts.
The STEER Traffic Simulator (Signals/Traffic Emulator with Event-based Responsiveness) is a program intended to simulate traffic on an urban network, modeling up to tens of thousands of vehicles.
METROPOLIS 1.0 is a modular system for Dynamic Traffic Simulations: It is aimed towards on-line as well as off-line simulations of traffic flows in an urban context and for large networks.
SmartPath simulation and animation package for traffic studies. See also Smart AHS a specification, simulation and evaluation framework for modeling, control and evaluation of Automated Highway Systems (AHS). Both part of California's PATH (Partners for Advances Transit and Highways)
Demonstration of Traf-Netsim for Traffice Operations Management: Final Report (1991) by Joan D. Sulzberg and Michael J. Demetsky. A "microscopic level" simulation of cars, buses and pedestrians.
Elevator Demos an individual-based simlulation model of a set of elevators in a ten story building. Uses a Java applet graphical front-end and a MODSIM III back-end running on a remote server.
Animation and Interactive Multimedia
The boids model of coordinated group motion such as flocks, herds and schools by Craig Reynolds. See also these demos of other related steering behaviors.
Artificial Animals for Computer Animation: Biomechanics, Locomotion, Perception, and Behavior (Ph.D Dissertation, 1996) by Xiaoyuan Tu. A biologically plausible, physically based model of fish ethology at the individual level.
The Virtual Fishtank is an interactive museum exhibit developed (by The Computer Museum, MIT Media Lab, and NearLife Inc.) to introduce visitors to the phenomena of emergence and ideas from the sciences of complexity. See also these pages about The Virtual Fishtank at MIT and NearLife.
Related topics
Stochastic Spatial Models: A Hyper-Tutorial by Rick Durrett covers stochastic spatial models and their applications to biology.
Annotated list of links related to metapopulation biology, spatial population biology, landscape ecology by Dag Hjermann
Distributed Modular Spatial Ecosystem Modeling by Thomas Maxwell and Robert Costanza of the International Institute for Ecological Economics, and see the related Spatio-Temporal Modeling Page
WWW-Server for Ecological Modeling at the University of Kassel
A Multiple-Mechanism Developmental Model for Defining Self-Organizing Geometric Structures (1995) by Kurt Fleischer simulates the self-organization of structures in space at the level of individual "cells". See some images from this work.
MOSAIC: Simulation Modeling and Analysis of Cellular Interactions (warning, that is a traslation of the subtitle by a non-French-speaking American (me)).
Internet Ecologies Area at Xerox Palo Alto Research Center
Multi-robot systems:
Many-Robot Systems a US Navy site with a collection of papers about systems involving multiple robots. Explores collective action, cooperation, communication and self-organization.
Intelligent Methods for Multi-Agent Environments (1997) by Cem Ünsal. Presentation on self-organization and cooperation in natural and robotic groups.
Self-Organization in Large Populations of Mobile Robots (1993) by Cem Ünsal. Describes the use of a homogeneous population of robots, an Army-ant swarm, for transportation of material.
The Ants: A Community of Microrobots and their social behavior
The Amorphous Computing group at MIT explores issues such as "How do we obtain coherent behavior from the cooperation of large numbers of unreliable parts that are interconnected in unknown, irregular, and time-varying ways?"
Co-ordination in Artificial Agent Societies Social Structures and Its Implications for Autonomous Problem-Solving Agents (1999) by Sascha Ossowski
Microsimulation links at CRESS Centre for Research on Simulation in the Social Sciences
Mirror Worlds: Or the Day Software Puts the Universe in a Shoebox...How It Will Happen and What It Will Mean (1991) by David Gelernter. See also this bio of Gelernter and this review of Mirror Worlds in CTHEORY.
Web-Based Simulation links by Paul Fishwick, and A Survey of Web-Based Simulation by Ernie Page
Offline resources
Books
Individual-Based Models and Approaches in Ecology: Populations, Communities and Ecosystems, by Donald L. Deangelis, Louis J. Gross (Editors), published in 1992 by Chapman and Hall.
The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration by Robert Axelrod, published in 1997 by Princeton University Press. See also this online supplement.
Simulating Organizations: Computational Models of Institutions and Groups (1998) edited by Michael Prietula, Kathleen Carley and Les Gasser.
Turtles, Termites, and Traffic Jams Explorations in Massively Parallel Microworlds (1997) by Mitchel Resnick
How Hits Happen--Forecasting Predictability in a Chaotic Marketplace (1998) by Winslow Farrell, with foreword by Brian Arthur. Using agent-based models to simulate the consumers of pop culture. Find it at Amazon.com or ACSES.
Laboratories and Groups
Academic
Dynamic Landscape Simulation Modeling group of the Geographic Modeling Systems Laboratory at UIUC. See the page on Dynamic, Spatial, Ecological Modeling with links to spatially explicit models related to birds at Fort Hood, the desert tortoise, and a quasi-individual-based model of the sage grouse.
ECOTOOLS (and WESP) at the University of Oldenburg, develop tools to support the modeling and simulation of individual-oriented ecological models.
Wildlife Habitat Analysis Lab of the Department of Wildlife & Fisheries Sciences at Texas A&M University. See these Research Summaries.
Center for Computable Economics at University of California, Los Angeles. See for example Agent Based Simulations as a tool in Economics.
The Sony Computer Science Laboratory Paris has a research project on evolutionary linguistics which make use of indivudual-based models to study the emergence of language and meaning.
Project for the Simulation of Social Behaviour within the Italian National Research Council - Institute of Psychology. Within this program, formal models of interactions among intelligent autonomous agents have been developed and some computer simulation studies have been conducted.
Centre for Policy Modelling at Manchester Metropolitan University, especially the Special Interest Group on Agent Based Social Simulation.
Commercial
The Emergent Systems Group of PricewaterhouseCoopers uses multiple agent systems to model decision making and trends in various simulations of real world marketplaces. See Flight Simulators for Management (BusinessWeek 1998: "computer models may give execs previews of how decisions pan out") and Playing the game of life (Forbes 1997).
Thinking Tools uses Agent Based Adaptive Simulation technology to create the management equivalent of flight simulators to help train business decision-makers on a risk-free "practice field". An early project was TeleSim.
Journals
Journal of Artifical Societies and Social Simulation (JASSS)
Conferences
Past
Economic Simulation Conference Conference Proceedings February 9-10, 1996.
From Animals To Animats (SAB98) Fifth International Conference of the Society for Adaptive Behavior, University of Zurich, August 17-21 1998, Zurich, Switzerland.
Sixth International Conference on Artificial Life (Alife VI) June 27-29, 1998, University of California, Los Angeles, USA.
Multi-Agent Systems and Agent-Based Simulation (MABS 98) one of the eight meetings (including Third International Conference on Multi-Agent Systems (ICMAS 98)) comprising Agents' World
First International Conference on Virtual Worlds, July 1-3, 1998, International Institute of Multimedia, Paris, France.
Local Interaction and Global Phenomena in Vegetation and Other Systems, April 19-23, 1999, Institute for Mathematics and its Applications, University of Minnesota
Future
Workshop on Traffic and Granular Flow '99, September 27-29, 1999, University of Stuttgart, Germany.
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