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Westervelt1997"| Westervelt1997 Westervelt1997 Westervelt1999U Westervelt2002 Westervelt2002 White1995" White2000 Wilshusen2000a Wilshusen2000\ Zanon2004 Zellner2002>ZellnerIn Press  DHZo Jk +nP78k8 "|P6l ----ctrl1Dkq@macswpcn\`@ \\Ġ6macscntl@macscwdf@&macscwfc@.macsdref@macsmode@macsshnd@> Authors9Journals $Keywords "                               H  p Abel, NickAgarwal, Chetan Aikman, DavidAlberti, Marina Alexandridis, Konstantinos T.Allerd, Dana Kilbourne Amon, Georges Anas, A.pAndrew Wong H.H. Angelsen, A.Anh, Hoang Lan Anselin, Luc Antona, M.Antona, MartineAquino (d'), P. Arnott, R.Arnott, Richard Aronovich, S.Asakawa, TasiaAttonaty, J.M. Auber, S. Axtell, R.L.Axtell, Robert Aycrigg, J. Babin, D. Bah, A.p Bakam, I.Balan, Gabriel Catalin Balmann, A Balmann, A. Baron, C.Barreteau, F. O. Barreteau, O.Baskaran Krishnapillay Batty, M.Batty, Michael Becu, N.p Benenson, I.Berger, ThomasBernard, Robert N. 0 Bian, Ling Bieri, JoanneBockstael, Nancy Bogle, Rian Boissau, S. Bommel, P.Bommel, PierreBonnefoy, J.-L. Bousquet, F.Bousquet, Francois(Bousset, Jean Paul h Box, PaulBrail, Richard K.Briassoulis, Helen 0 Brondizio, E.Brondizio, Eduardo 0 Brown, D. Brown, D. G.Brown, Daniel G.Bruch, Elizabeth E. 0 Button, K. Carr, Eric Caruso, G Castella, J.CCastella, J.C. Cherry, Susan Chinembri, F. Chladek, P.Cioffi-Revilla, ClaudioCojocaru, George Collier, N.Common, Michael d'Aquino, P.Daniel, Terry C.Davidsson, Paul Deadman, P. Dean, J.S.Deffuant, Guillaume hDesyllas, Jake Dibble, C. Dieckman, U. Dijst, M. Drazan, P.Dreyfus-Leon, Michel Ducrot, R. Duijn, M.Duke-Sylvester, Scott M.Duxbury, Elizebeth E. Soepadmo Engelen, G. Epstein, J.M.Epstein, Joshua M. 0 Etienne, M.(%Etienne, M., Le Page, C. and Cohen, M Evans, T. Evans, T. P. Evans, Tom F. BousquetFeldman, Philip G. 0Fernandez, L. E.Fernandez, Luis E. hFeuillette, S. Fleming, MarkFlorax, Raymond J. G. M. Foster, DavidFoster, David R. Gautier, D. Geist, H.Geoghegan, JacquelineGilbert, NigelGimblett, H. RGimblett, H. Randy Gimblett, R. Ginot, V.Goodchild, Michael F. Gotts, N. M. Gotts, N.M. Gotts, N.M.G.Green, Glen M. Grimm, VolkerGross, Louis J.Grove, J. Morgan Guizol, PGumerman, G.J.Gumerman, George J.(Hannon, Bruce M. Happe, K. Harper, S. J.Harper, Steve J.Harper, Steven J. Haynes, K.Henriot, Jrme Hensher, D. Hesper, b. Hirst, K.;Hirst, Kathleen M. 0 Hoffmann, M Hogeweg, P.Hopkins, L. D. Huet, Sylvie Immers, L.H. Irwin, ElenaIrwin, Elena G. Itami, R.Itami, Robert M.Janssen, M. A.  ,$Agricultural Economics,'Agriculture, Ecosystems and Environment41Annals of the Association of American Geographers,(Annual Review of Environmental Resources($Behavioural Ecology and Sociobiology Bioscience40Computational & Mathematical Organization Theory,(Computers, Environment and Urban Systems,)Computers, Environment, and Urban SystemsConservation Ecology@ CyberGo@Cybernetics and SystemsEcological Modelling` Environment and Planning B%G($Environmental Modelling and Software,'Environmental Monitoring and Assessment,)European Review of Agricultural Economics Geoforum@ GeoJournalIntegrated Assessment<7International Journal of Geographic Information Systems<9International Journal of Geographical Information Science85Journal of Artificial Societies and Social Simulation,(Journal of Economic Dynamics and Control Journal of Economic Geography$Journal of Economic Literature"G(#Journal of Environmental Management Journal of Geographic Systems4.Journal of Mathematical and Computer Modelling$Journal of Nature Conservation"G,(Lecture Notes in Artificial Intelligence4.Quarterly Journal of International AgricultureSimulations and Gaming$ The World Bank Research Observer$Trends in Ecology and Evolution=` Urban Studies      "!X#z B HBW. Rand M. Zellner S. E. Page R. Riolo D. G. Brown L. E. Fernandez 2002TNThe Complex Interaction of Agents and Environments: An Example in Urban Sprawl Agent 2002  Chicago, ILv "Argonne National Laboratory http://agent2002.anl.gov/@:Rouchier, J. F. Bousquet, M. Requier-Desjardins M. Antona 2001{A multi-agent model for describing transhumance in North Cameroon: Comparison of different rationality to develop a routinei.(Journal of Economic Dynamics and Control25527-559tSchelling, Thomas C. 1978$Mircomotives and Macrobehavior.'Fels lectures on public policy analysisi New York  W. W. Norton 81Trame, A. Harper, S. J. Aycrigg, J. Westervelt, Jt 1997nhThe Fort Hood Avian Simulation Model: A Dynamic Model of Ecological Influences on Two Endangered Species Champaign, Ill. *#U.S. Army, Corps of Engineers, CERL 97/88trame9760http://blizzard.gis.uiuc.edu/dsm_FHASM_frame.htm Verburg, P. Veldkamp, A. FothcomingJCSpecial land-use modeling issue of the International Journal of GISa HBWestervelt, James D. Hannon, Bruce M. Levi, Shaun Harper, Steve J. 1997rkA Dynamic Simulation Model of the Desert Tortoise (Gopherus agassizii) Habitat in the Central Mojave Desert  Champaign, IL *#U.S. Army, Corps of Engineers, CERL 97/102 westervelt976/http://blizzard.gis.uiuc.edu/dsm_TORT_frame.htmWhite, R. Engelen, G. 2000\UHigh-resolution integrated modeling of spatial dynamics of urban and regional systemsy0)Computers, Environment, and Urban Systemse24383-400  $"Agent architecturesO8agent-based modeling CORMASipaDecision-making process  Fisheries ABMgeo-spatial relationsHDGeographic Automata Systems, cellular automata, multi-agent systems,8TNGeographic Information Science, geosimulation, Geographic Information Systems,O heuristicsd mhuman behaviorlatIBMO8Individual-based models land use/cover transformation lc_abm^0 lc_intro lc_stats lc_vandvLUCC0LUCC, ADSS, lc_abmLUCC, ADSS, manson_cv(#LUCC, modeling methodology,lc_intro#Model Validationmodeling methodologyMulti-agent systemsO84.Object-Oriented Programming, urban simulation. OrganizationsParticipatory ABMpath dependencePedestrian modelingO power lawsd mRBsim Simulationt s spat_abmtropical regionsr<SRQ(ON%vv:4H. Randy Gimblett Merton T. Richards Robert M. Itami 2002rlSimulating Wildland Recreation Use and Conflicting Spatial Interactions using Rule-Driven Intelligent Agents H. Randy Gimblettt}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes  Oxford, UK Oxford University Press Gimblett, H. R 2002}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes  Oxford, U.K. Oxford University Press lc_abmGimblett, H. Randy 2002Integrating Geographic Information Systems and Agent-Based Technologies for Modeling and Simulating Social and Ecological Phenomena Gimblett, H. R}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processesx  Oxford, U.K. Oxford University Press 1-20 lc_abmGimblett, H. Randy Roberts, Catherine A. Daniel, Terry C. Ratcliff, Michael Meitner, Michael Cherry, Susan Stallman, Doug Bogle, Rian Allerd, Dana Kilbourne Bieri, Joanne 2002An intelligent agent model for simulating and evaluating river trip scenarios along the Colorado River in Grand Canyon National Park Gimblett, H. R}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes  Oxford, U.K. Oxford University Pressm245-276 lc_abmGimblett, H. Randy 2003>8Personal Communication: Input regarding modeling and GISSept. 19, 2003 e-mail&Ginot, V. C. Le Page S. Souissi 2002NGMulti-agents architecture to enhance enduser individual-based modeling.Ecological Modelling 157 23-41 IBM,%Gotts, N.M. Polhill, J.G. Law, A.N.R. 20030*Aspiration levels in a land use simulationCybernetics and Systems34663-683gotts03"Gotts, N.M. Parker, Dawn C.In preparation\VPower law size distributions of rural land holdings in real and simulated environments Cioffi-Revilla, ClaudiotmPower Laws in the Social Sciences: Discovering Complexity and Non-Equilibrium Dynamics in the Social Universetgotts_parker_pl @ -.$02145 7;89=?>@ABD C E'F GHIJKNOR%QSUVW[\Z^_`bcdfghjklortqvpxz{ }~#!"cience to unite cellular automata and multi-agent systems techniques, and provides a spatial approach to bottomup modeling of complex geographic systems that are comprised of infrastructure and human objects. The suitability of the framework is also discussed with reference to existing cellular automata and multi-agent systems models used in urban studies. Practical implementation of the framework is illustrated with reference to an object-based urban simu?w;_p"3пtY@ 0 p0Ub8U Mikesell, S. 0 UyX  "#NU"$ Y@t Y@ H"L"<U"=8 Y@ ") ") Y@ t p"3пtY@ 0 p0Ub8UDieckman, U. Law, R. Metz, J. A. J. 2000.'The Geometry of Ecological Interactions "Dieckman, U. Metz, J. A. J.,&Cambridge Studies in Adaptive Dynamics  Cambridge, UK Cambridge University Press1Individual-based models.'Engelen, G. R. White I. Unjee P. Drazan 1995~xUsing cellular automata for integrated modelling of socio-environmental systems, environmental monitoring and assessment.'Environmental Monitoring and Assessment?34203-214 @ &$ ' % #!"5{@KW|????>>>===<<_d_Q888777666555444333222111000///...---,,,+++***)))((('''&&&%%%$$$###"""!!!  RF?An integrated urban development and ecological simulation modele"Marina Alberti Paul WaddellIntegrated AssessmentlAlbertia1d 2000 2000215-2273 82Alexandridis, Konstantinos T. Pijanowski, Bryan C. 2002~xMulti agent-based environmental landscape (MABEL) -- an artifical intelligence simulation model: some early assessments East Lansing, MI Michigan State University 1-26 June 2002t@:Department of Agricultural Economics -- Staff Paper SeriesStaff Paper 2002-09hbagent-based modeling heuristics land use/cover transformation geo-spatial relations human behavior~xPresented at the AERE/EAERE: 2002 World Congress of Environmental and Resource Economics, Monterey, CA, June 24-27-2002K0JIH$G&Joshua M. Epstein Robert Axtelle 1996F?Growing Artificial Societies: Social Science from the Ground Upu Washington, D.C. "Brookings Institution Press7 1996 epstein96o,%Etienne, M., Le Page, C. and Cohen, M 2003|A step-by-step approach to building land management scenarios based on multiple viewpoints on multi-agent system simulations<5Journal of Artificial Societies and Social SImulation62Participatory ABM CORMASA multi-agent system was developed to simulate strategies of natural resource management in the Causse Mjan, a limestone plateau dominated by a rare grassland-dominated ecosystem endangered by pine invasion. To stimulate the emergence of alternative long-term management strategies for the sheep farms and the woodlands, contrasting dynamic viewpoints on land resources were designed at different space scales. To begin with, they were individually used to validate the model with each type of main stakeholders (foresters, farmers and the National Park of Cvennes rangers), to improve it and to propose individual scenarios of natural resource management. Once the model improved, the set of viewpoints made it possible to assess the impact of the individual scenarios on the main productive (sheep stocking rate, timber growth) and environmental (endangered species, landscape value) stakes on any spatial entity considered as relevant by any stakeholder. As the different opinions were collectively viewed and confronted, the need to agree to a compromise was highlighted and led to new scenarios based on more collective management of the pine woodlands. The results of these alternative scenarios were collectively evaluated anew and it was then possible to select a set of feasible scenarios stemming from current actors' perceptions and practices and to suggest alternative sylvopastoral management based on innovative practices. The paper underlines the usefulness of the representation of viewpoints in that it allowed for scenario description and impact assessment of the compared management strategies. It also shows how the step-by-step approach contributed to improve decision-making by National Park managers.Required.(http://jasss.soc.surrey.ac.uk/6/2/2.html Etienne, M. 2003zsSylvopast: A multiple target role-playing game to assess negotiation processes in sylvopastoral management planning<5Journal of Artificial Societies and Social SImulation62.(http://jasss.soc.surrey.ac.uk/6/2/5.htmlEvans, T. P. Kelley, H.In Press<6Scale Issues in Agent-Based Models of Landcover Change*#Journal of Environmental Management<5Fernandez, L. E. Brown, D. Marans, R.W. Nassauer, J.I In Review>jcCharacterizing location preferences in an exurban population: Implications for agent based modeling Environment and Planning BXRhttp://www.pscs.umich.edu/research/projects/sluce/publications/Fernandez_et_al.pdf2+Feuillette, S. Bousquet, F. Le Goulven, P.; 2003d]Sinuse: A multi-agent model to negotiate water demand management on a free access water table*$Environmental Modelling and Software18413-427.(Nigel Gilbert Sarah Maltby Tasia Asakawa 2002^WParticipatory Simulations for Developing Scenarios in Environmental Resource Managementt Christoph Urbane,&3rd Workshop on Agent-Based Simulation Ghent, Belgium $SCS-European Publishing Housep 67-72ae semi-arid areas of ZimbabweF  M. A. Janssen\VComplexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches (!Cheltenham, U.K.; Northampton, MAp Edward Elgar Publishersb Steven Mansont 2001<5Simplifying complexity: A review of complexity theoryGeoforum323405-414 2001manson01Manson, Steven M.y Forthcoming HAThe SYPR integrative assessment model: Complexity in development :4Turner II, B. L. Foster, David Geoghegan, JacquelineZTFinal Frontiers: Understanding Land Change in the Southern Yucatan Peninsular Region  Oxford, UK & Claredon Oxford University PressLUCC, ADSS, manson_cvn 2,Parker, Dawn C. Berger, Thomas Manson, S. M. 2002f`Agent-Based Models of Land-Use/Land-Cover Change: Report and Review of an International Workshop Bloomington, IN\  LUCC Focus 1LUCC Report Series6 lc_abm<6http://www.indiana.edu/~act/focus1/FinalABM11.7.02.pdfJDParker, Dawn C. Manson, S. M. Janssen, M. A. Hoffmann, M Deadman, P. 2003XRMulti-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review81Annals of the Association of American Geographers932 lc_abmPIhttp://www.csiss.org/events/other/agent-based/papers/maslucc_overview.pdft"Parker, Dawn C. Meretsky, V. ForthcomingleMeasuring Pattern Outcomes in an Agent-Based Model of Edge-Effect Externalities Using Spatial Metrics.'Agriculture, Ecosystems and Environment lc_abmHAhttp://php.indiana.edu/~dawparke/papers/aee_final/parker_text.pdf K. S. Rajan R. Shibasaki 2000TMLand Use/Cover Changes and Water Resources - Experiences from AGENT-LUC Model  Tokyo, Japan ~wInternational Center for Disaster Mitigation Engineering (INCEDE), Institute of Industrial Science, University of Tokyo 1-16 Oct.Conference Proceedings19B;http://incede.iis.u-tokyo.ac.jp/reports/Report_19/Rajan.pdf VF4' E~H ,DC^ FBA@?>=:hbBrown, D. Collier, N. Johnston, K. Miller, D. Najlis, R. North, M. Rand, W. Riolo, R. Robinson, D. 2004PIPersonal Communication: Agent Analyst ArcGIS Extension, Under DevelopmentMarch-July, 2004`YJoint Argonne National Lab, ESRI, and Univeristy of Michigan software development project>7Brown, D. G. Page, S.E. Riolo, R. Zellner, M. Rand. W.In PressTMPath dependence and the validation of agent-based spatial models of land use.>7International Journal of Geographic Information Systemsbrown04`Zpath dependence Model Validation agent-based modeling land use/cover transformation lc_abmZThttp://www.pscs.umich.edu/research/projects/sluce/publications/ijgis-sluce-final.pdf:3Brown, D. North, M. Robinson, D. Riolo, R. Rand, W.In PressXQSpatial Process and Data Models: Toward Integration of Agent-Based Models and GIS$Journal of Geographic Systems May, 2004B;http://www.cscs.umich.edu/sluce/publications/jgs_abmgis.pdf("Bruch, Elizabeth E. Robert D. Mare 2004ZSComputational and Statistical Models for Residential Choice and Neighborhood ChangeB.(Duke-Sylvester, Scott M. Gross, Louis J. 2002Integrating spatial data into an agent-based modeling system: ideas and lessons from the development of the Across-Trophic-Level System Simulation Gimblett, H. R~Integrating Geographic Information Systems and Agent-based Modeling Techniques for Simulating Social and Ecological Processes Oxford Oxford University Press>8Santa Fe Institute Studies in the Sciences of Complexity duke02.'Engelen, G. R. White I. Unjee P. Drazan 1995~xUsing cellular automata for integrated modelling of socio-environmental systems, environmental monitoring and assessment.'Environmental Monitoring and Assessment?34203-214L.-bHAMartine Antona Pierre Bommel Francois Bousquet Christophe Le Page 2002Interactions and Organization in Ecosystem Management: The Use of Multi-Agent Systems to Simulate Incentive Environmental Policies Christoph Urban ,&3rd Workshop on Agent-Based Simulation Ghent, Belgium $SCS-European Publishing Housed 85-9281Aquino (d'), P. Le Page, C. Bousquet, F. Bah, A. 2003Usings self-designed role-playing games and a multi-agent system to empower a local decision-making process for land use management: The selfcormas experiment in Senegal<5Journal of Artificial Societies and Social SImulation63Participatory ABM CORMASRequired0* Balmann, A.1 199782Farm-based modelling of regional structural change0)European Review of Agricultural Economicse251e 85-108 lc_abmBalmann, A. Happe, K. 2000f`Applying parallel genetic algorithms to economic problems: the case of agricultural land marketsxqIIFET 2000: Microbehavior and Macroresults, Proceedings, International Institute of Fisheries Economics and Trade balmann00f4.Balmann, A K. Happe K. Kellermann A. Kleingarn 2003VPAdjustment costs of agri-environmental policy switchings: A multi-agent approach  M. A. Janssen \VComplexity and Ecosystem Management: The Theory and Practice of Multi-agent Approaches (!Cheltenham, U.K.; Northampton, MAp Edward Elgar Publishers7 5.B4h210$.N.'Barreteau, O. F. Bousquet J.M. Attonaty 2001Role-playing games for opening the black box of multi-agent systems: method and lessons of its application to Senegal River Valley irrigated systems<5Journal of Artificial Societies and Social Simulation42.(http://jasss.soc.surrey.ac.uk/4/2/5.html.(Barreteau, O. LePage, C. Aquino (d'), P. 2003:4Role-Playing Games, Models and Negotiation Processes<5Journal of Artificial Societies and Social Simulation62  barreteau03Participatory ABM CORMASRequired0)http://jasss.soc.surrey.ac.uk/6/2/10.html Batty, M. 2001&Agent-based pedestrian modeling\ Environment and Planning B283321-3262+Batty, M. Desyllas, Jake Duxbury, Elizebeth 2003^WSafety in numbers? Modelling crowds and designing control for the Notting Hill carnival Urban Studies408 1573-1590 Pedestrian modeling>7Becu, N. Perez, P. Walker, B. Barreteau, O. Le Page, C. 2003|vAgent-based simulation of a small catchment water management in northern Thailand: Description of the catchscape modelEcological Modelling 170319-331 Benenson, I. 1998@:Multiagent simulations of residential dynamics in the city.(Computers, Environment and Urban Systems221 25-42Benenson, I. Torrens, P. 2004@9Geosimulation: Automata-Based Modeling of Urban Phenomena London John Wiley & Sons(!Benenson, I. S. Aronovich S. NoamIn PressRLLet's talk objects: generic methodology for urban high-resolution simulation0)Computers, Environment, and Urban Systems\Berger, Thomas 2001Agent-based spatial models applied to agriculture: A simulation tool for technology diffusion, resource use changes, and policy analysisAgricultural Economics25 2-3245-260? September@$Berger, Thomas Parker, Dawn C. 20024-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  Santa Barbarai  CIPEC/CSISS CIPEC Collborative Report lc_abm0)http://www.csiss.org/maslucc/ABM-LUCC.htm&Berger, Thomas Ringler, Claudia  2002|Trade-offs, efficiency gains and technical change - modeling water management and land use within a multiple-agent framework4.Quarterly Journal of International Agriculture41 1/2119-144berger02 Bian, Ling 2004^WA conceptual framework for an individual-based spatially explicit epidemiological model Environment and Planning B31381-395spat_abmtnAbstract. This paper presents a conceptual framework to formalize an individual-based and spatially explicit model of the epidemiology of infectious diseases. The framework differs from that of the traditional population-based epidemiological models in terms of assumptions, conceptual models, and model structures. In particular, the author discusses four aspects of the model: (1) population segments or unique individuals as the modeling unit, (2) continuous process or discrete events to represent the disease development through time, (3) traveling wave or network dispersion to represent the disease transmission in space, and (4) within-group and between-group interactions to represent local and long-distance transmissions. Based on these conceptual discussions, a simple influenza epidemic is simulated in order to illustrate the application of the proposed framework. Required. Boissau, S. Castella, J.C 2003Constructing 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 methodologySimulations and Gaming343342-347 0*Bousquet, F. I. Bakam H. Proton C. Le Page 1998<5Cormas: Common-pool resources and multi-agent systems.(Lecture Notes in Artificial Intelligence 1416826-837e Bousquet, F. Gautier, D. 1998Comparaison de deux approches de modlisation des dynamiques spatiales par simulation multi-agents : Les approches spatiales et acteurs\CyberGo8982http://193.55.107.45/modelis/bousquet/bousquet.htm;v 984-Bousquet, F. Le Page, C. Antona, M. Guizol, P 2000F@Ecological scales and use rights : The use of multiagent systems Baskaran Krishnapillay, E. Soepadmo, Najib Lotfy Arshad, Andrew Wong H.H., S. Appanah, Suhaimi Wan Chik, N. Manokaran, Hong Lay Tong Khoo Kean Choon,f_Forest and society : The role of research. Sub-plenary session XXI. IUFRO world congress 2000  Kuala Lumpu,4.Bousquet, F. LePage, C. Bakam, I. Takforyan, A 2001TNMulti-agent simulations of hunting wild meat in a village in eastern cameroonEcological Modelling 138331-346pjBousquet, F. F. O. Barreteau P. d'Aquino M. Etienne S. Boissau S. Auber C. Le Page D. Babin J.C. Castella 2003RKMulti-agent systems and role games: An approach for ecosystem co-management  M. A. Janssen6/Multi-Agent Approaches for Ecosystem ManagementBousquet, F. Le Page, C. 2004@:Multi-agent simulations and ecosystem management: a reviewEcological Modelling76 3-4313-332b[Multi-agent systems; Simulation; Organization; Agent architectures; Decision-making processb[This paper proposes a review of the development and use of multi-agent simulations (MAS) for ecosystem management. The use of this methodology and the associated tools accompanies the shifts in various paradigms on the study of ecological complexity. Behavior and interactions are now key issues for understanding and modeling ecosystem organization, and models are used in a constructivist way. MAS are introduced conceptually and are compared with individual-based modeling approaches. Various architectures of agents are presented, the role of the environment is emphasized and some computer tools are presented. A discussion follows on the use of MAS for ecosystem management. The strength of MAS has been discussed for social sciences and for spatial issues such as land-use change. We argue here that MAS are useful for problems integrating social and spatial aspects. Then we discuss how MAS can be used for several purposes, from theorization to collective decision-making support. We propose some research perspectives on individual decision making processes, institutions, scales, the credibility of models and the use of MAS. In conclusion we argue that researchers in the field of ecosystem management can use multi-agent systems to go beyond the role of the individual and to study more deeply and more effectively the different forms of organization (spatial, networks, hierarchies) and interactions among different organizational levels. For that objective there is considerably more fruit to be had on the tree of collaboration between social, ecological, and computer scientists than has so far been harvested.Required "vBtZ`rNq~4p&Parker, Miles T. 2001.'What is Ascape and Why Should You Care? <5Journal of Artificial Societies and Social SImulation41\VAscape is a framework designed to support the development, visualization, and exploration of agent based models. In this article I will argue that agent modeling tools and Ascape, in particular, can contribute significantly to the quality, creativity, and efficiency of social science simulation research efforts. Ascape is examined from the perspectives of use, design, and development. While Ascape has some unique design advantages, a close examination should also provide potential tool users with more insight into the kinds of services and features agent modeling toolkits provide in general..(http://jasss.soc.surrey.ac.uk/4/1/5.html 2,Parker, Dawn C. Berger, Thomas Manson, S. M. 2002f`Agent-Based Models of Land-Use/Land-Cover Change: Report and Review of an International Workshop Bloomington, IN\  LUCC Focus 1LUCC Report Series6 lc_abm<6http://www.indiana.edu/~act/focus1/FinalABM11.7.02.pdf2,Parker, Dawn C. Manson, S. M. Berger, Thomas 2002<6POTENTIAL 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  Santa Barbara  CIPEC/CSISS CIPEC Collborative Report lc_abm0)http://www.csiss.org/maslucc/ABM-LUCC.htm 2,Parker, Dawn C. Berger, Thomas Manson, S. M. 2002|Meeting the Challenge of Complexity: Proceedings of the Special Workshop on Agent-Based Models of Land-Use/Land-Cover Change  Santa Barbara  CIPEC/CSISS CIPEC Collborative Report CCR-3 lc_abm0)http://www.csiss.org/maslucc/ABM-LUCC.htmJDParker, Dawn C. Manson, S. M. Janssen, M. A. Hoffmann, M Deadman, P. 2003XRMulti-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review81Annals of the Association of American Geographers932 lc_abmRequiredPIhttp://www.csiss.org/events/other/agent-based/papers/maslucc_overview.pdf Parker, Dawn C. Caruso, G 2003}Linking Local Spatial Externalities and Urban Sprawl: A Comparison of Two Agent-Based Cellular Automaton Modeling ApproachesTNNorth American Association for Computational Social and Organizational Science Pittsburgh, PA June 22-252,http://www.casos.ece.cmu.edu/conference2003/"Parker, Dawn C. Meretsky, V. 2004leMeasuring Pattern Outcomes in an Agent-Based Model of Edge-Effect Externalities Using Spatial Metrics.'Agriculture, Ecosystems and Environmenti 101233-250 lc_abmRequiredHAhttp://php.indiana.edu/~dawparke/papers/aee_final/parker_text.pdfParker, Dawn C.Under RevisionrkIntegration of Geographic Information Systems and Agent-Based Models of Land Use: Challenges and Prospects :3David J. Maguire Michael F. Goodchild Michael Batty("GIS, Spatial Analysis and Modeling  Redlands, CA  ESRI Press0)Polhill, J. G. Gotts, N. M. Law, A. N. R.S 2001HAImitative versus nonimitative strategies in a land use simulationCybernetics and Systems32 1-2285-307\ polhill01 K. S. Rajan R. Shibasaki 2000TMLand Use/Cover Changes and Water Resources - Experiences from AGENT-LUC Model  Tokyo, Japan ~wInternational Center for Disaster Mitigation Engineering (INCEDE), Institute of Industrial Science, University of Tokyo 1-16 Oct.Conference Proceedings19B;http://incede.iis.u-tokyo.ac.jp/reports/Report_19/Rajan.pdf WVZU`<SRQ(ON%:4H. Randy Gimblett Merton T. Richards Robert M. Itami 2002rlSimulating Wildland Recreation Use and Conflicting Spatial Interactions using Rule-Driven Intelligent Agents H. Randy Gimblettt}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes  Oxford, UK Oxford University Press Gimblett, H. R 2002}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes  Oxford, U.K. Oxford University Press lc_abmGimblett, H. Randy 2002Integrating Geographic Information Systems and Agent-Based Technologies for Modeling and Simulating Social and Ecological Phenomena Gimblett, H. R}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processesx  Oxford, U.K. Oxford University Press 1-20 lc_abmGimblett, H. Randy Roberts, Catherine A. Daniel, Terry C. Ratcliff, Michael Meitner, Michael Cherry, Susan Stallman, Doug Bogle, Rian Allerd, Dana Kilbourne Bieri, Joanne 2002An intelligent agent model for simulating and evaluating river trip scenarios along the Colorado River in Grand Canyon National Park Gimblett, H. R}Integrating Geographic Information Systems and Agent-Based Modeling Techniques for Simulating Social and Ecological Processes  Oxford, U.K. Oxford University Pressm245-276 lc_abmGimblett, H. Randy 2003>8Personal Communication: Input regarding modeling and GISSept. 19, 2003 e-mail&Ginot, V. C. Le Page S. Souissi 2002NGMulti-agents architecture to enhance enduser individual-based modeling.Ecological Modelling 157 23-41 IBM,%Gotts, N.M. Polhill, J.G. Law, A.N.R. 20030*Aspiration levels in a land use simulationCybernetics and Systems34663-683gotts03"Gotts, N.M. Parker, Dawn C.In preparation\VPower law size distributions of rural land holdings in real and simulated environments Cioffi-Revilla, ClaudiotmPower Laws in the Social Sciences: Discovering Complexity and Non-Equilibrium Dynamics in the Social Universetgotts_parker_pl:4Steven J. Harper James D. Westervelt Ann-Marie Trame 2002b[Management application of an agent-based model : control of cowbirds at the landscape scale Gimblett, H. RIntegrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes Oxford University Press$Hoffmann, M H. Kelley T. Evans 2003tnSimulating land-cover change in South-Central Indiana: An agent-based model of deforestation and afforestation  M. A. Janssen\VComplexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches (!Cheltenham, U.K.; Northampton, MAp Edward Elgar Publishers"Elena Irwin Nancy Bockstaeld 2002d]Interacting agents, spatial externalities, and the evolution of residential land use patterns$Journal of Economic Geography0211 31-54 Jan0irwin01lc_statsRequired `_^\[Zl^X Robert M. Itami Glen S. MacLaren Kathleen M. Hirst Robert J. Raulings H. Randy 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\U 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4) Banff, Alberta, CanadaSeptember 2 - 8{This paper describes advancements in recreation management using new technology that couples Geographic Information Systems (GIS) with Intelligent Autonomous Agents to simulate recreation behaviour in real world settings. RBSim is a computer program that allows park management to explore the consequences of change to any one or more variables so that the goal of accommodating increasing visitor use is achieved while maintaining the quality of visitor experience. RBSim provides both a qualitative understanding of management scenarios by the use of map graphics from a GIS as well as a quantitative understanding of management consequences by generating statistics during the simulation. Managers are able to identify points of over crowding, bottle necks in circulation systems, and conflicts between different user groups. RBSim is designed to be easy to use by park management staff. This is facilitated through a tight integration with MapInfo GIS which allows a practical solution for quickly building complex simulation models. Simulation techniques provide methods for evaluating details of management decisions as they impact visitors and the environment. No other analysis tool that achieves this level of understanding is currently available. The paper describes RBSim focussing on the parameters required to generate simulation models for existing and proposed park management scenarios@:http://www.colorado.edu/research/cires/banff/pubpapers/57/ Itami, R. 2002.'Mobile agents with spatial intelligence Gimblett, H. RIntegrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes Oxford University Pressl191-210XRItami, R. Raulings, R. MacLaren, G.. Hirst, K.; Gimblett, R. Zanon, D. Chladek, P. 2004haSimulating the complex interactions between human movement and the outdoor recreation environmentn$Journal of Nature Conservation114278-286 RBsimAB;Janssen, M. A. Walker, Brian H. Langridge, Jenny Abel, Nick 2000rkAn adaptive agent model for analysing co-evolution of management and policies in a complex rangeland systemEcological Modelling 131249-268! janssen00  Janssen, M.A 2003\VComplexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches (!Cheltenham, U.K.; Northampton, MA Edward Elgar Publishersb Janssen, M. A. Ostrom, E.T Forthcoming*#GOVERNING SOCIAL-ECOLOGICAL SYSTEMS Judd, K. Leigh TesfatsionRKHandbook of Computational Economics II: Agent-Based Computational Economics  North-Holland{Handbooks in Economics Required. Judson, O. P. 199481The rise of the individual-based model in ecologyp&Trends in Ecology and Evolutione91 9-14 Kaimowitz, D. Angelsen, A. 1998:3Economic Models of Tropical Deforestation: A Reviewi Jakarta, Indonesia 0*Centre for International Forestry Research 1998lc_introKelley, H. Evans, T. P. Under ReviewjdThe Relative Influence of Land-owner and Landscape Heterogeneity in an Agent-Based Model of Land Use Hfdzc~bTimothy A. Kohler 2000.'Dynamics in Human and Primate Societies0 New York and Oxfordl Oxford University Press.(SFI studies in the science of complexity 2000kohler00RKTimothy A. Kohler James Kresl Carla Van West Eric Carr Richard H. Wilshusene 2000Be there then: A modeling approach to settlement determinants and spatial efficiency among late ancestral pueblo populations of the Mesa Verde region, U.S. Southweste ,&Kohler, Timothy A. Gumerman, George J..'Dynamics in Human and Primate Societiess New York and Oxfordl Oxford Univeristy Press0145-178a.(SFI studies in the science of complexity("Michael Kwartler Robert N. Bernard 2001:3CommunityViz: An Integrated Planning Support System ,&Richard K. Brail Richard E. Klosterman^XPlanning Support Systems Integrating Geographic Systems, Models, and Visualization Tools("Lambin, E. F. Geist, H. Lepers, E. 2003 Z>Dynamics of land-use and land-cover change in tropical regions D(Annual Review of Environmental Resources 28 $205-241 T7land use/cover transformation tropical regions lc_intro Lansing, J. Stephenb 1993XRPriests and Programmers: Technologies of Power in the Engineered Landscape of Bali  Princeton, NJ{ Princeton University Press*$Lansing, J. Stephen Kremer, James N. 1993haEmergent Properties of Balinese Water Temple Networks: Coadaptation on a Rugged Fitness Landscapet Chris.G. LangtonArtificial Life III?  Reading, MA Addison-Wesley201-224@9Lim, K. Deadman, P. Moran, E. Brondizio, E. McCracken, S.- 2002d^Agent-based simulations of household decision making and land use change near Altamira, Brazil Gimblett, H. RIntegrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes  Oxford, U.K. Oxford University Press@TMSean Luke Gabriel Catalin Balan Liviu Panait Claudio Cioffi-Revilla Sean PausD 20032,MASON: A Java Multi-Agent Simulation Library Agent 2003  Chicago, IL.D>http://cs.gmu.edu/~eclab/projects/mason/papers/Agent2003.6.pdf Lynam, T. 2002~wScientific measurements and villagers' knowledge: an integrative multi-agent model from the semi-arid areas of Zimbabwe' Janssen, M. A.*#Complexity and Ecosystem Management Northampton, MA  Edward Elgar188-217lynam02 Lynam, T. 2003voComplex and useful but certainly wrong: A multi-agent agro-ecosystem model from the semi-arid areas of ZimbabweF  M. A. Janssen\VComplexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches (!Cheltenham, U.K.; Northampton, MAp Edward Elgar Publishersb decision making and land use change near Altamira, Brazil Gimblett, H. RIntegrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes  Oxford, U.K. Oxford University Press@ Long, J. S. 1997HARegression Models for Categorical and Limited Dependent Variables>7Advanced Quantitative Techniques in the Social Sciences Sage PublicationsTMSean Luke Gabriel Catalin Balan Liviu Panait Claudio Cioffi-Revilla Sean PausD 20032,MASON: A Java Multi-Agent Simulation Library Agent 2003  Chicago, IL.D>http://cs.gmu.edu/~eclab/projects/mason/papers/Agent2003.6.pdf Lynam, T. 2003voComplex and useful but certainly wrong: A multi-agent agro-ecosystem model from the semi-arid areas of ZimbabweF  M. A. Janssen\VComplexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches (!Cheltenham, U.K.; Northampton, MAp Edward Elgar Publishersb   Janssen, M.A Jianchu, X. Johnston, K. Judd, K.p Judson, O. P. Kaimowitz, D.Kellermann, K. Kelley, H.Khoo Kean ChoonKleibe, Pierre Kleingarn, A.Klosterman, Richard E. Kobti, Ziad Kohler, T.A.Kohler, Timothy A.(Kremer, James N. Kresl, James Kuper, MpKwartler, Michael Lambin, E. F.Langridge, JennyLangton, Chris.G.Lansing, J. Stephen( Law, A. N. R. Law, A.N.R. Law, R.PLe Goulven, P. Le Page, C. LePage, C. Lepers, E. Levi, Shaun Lim, K.p Loibl, W. Long, J. S.Longley, P. A. Luke, Sean Lynam, T. Ma, YuepMacal, C. M, . Macal, C.M. MacLaren, G..MacLaren, Glen S.Maguire, David J. Maltby, Sarah Manson, S. M.Manson, StevenManson, Steven M. Marans, R.W.Mare, Robert D.Marks, Barbara J. Mathevet, R. McCarroll, S. McCracken, S.McGarigal, KevinMcGilvray, JamesMcMillen, DanielMeitner, Michael Meretsky, V.Metz, J. A. J. Mikesell, S. Miller, D.Mombeshora, B. Moran, E. Moran, Emilio Moss, Scott N. ManokaranNajib Lotfy Arshad 0 Najlis, R. Najlis, R. I. Nassauer, J.I Noam, S.p North, M. Ostrom, E. Otter, H. S. Page, C. L. Page, C. LePage, Christophe Le( Page, S. E. Page, S.E.Page, Scott E. Panait, LiviuParker, Dawn C.Parker, Miles T. Parket, M.T. Paus, SeanPeerenboom, J. P. Perez, P. Perman, RogerPijanowski, Bryan C.(Polhill, J. G. Polhill, J.G. Proton, H.Railsback, Steven F. Rajan, K. S. Rand, W.p Rand, WilliamRatcliff, Michael Raulings, R.Raulings, Robert J. 0Requier-Desjardins, M.Reynolds, RobertRichards, Merton T. Rimmer, M.Ringler, Claudia Riolo, R. Riolo, RickRoberts, Catherine A. Robinson, D.Robinson, Derek Rouchier, J.Rouchier, Juliette hRounsevell, Mark S. Appanah Sasaki, YukaSchelling, Thomas C.( Schlager, E. Schot, P.Schweik, Charles Shibasaki, R.Shinawatra-Ekasingh, B. Small, K. A. Souissi, S. Souli, J.-C.Stallman, DougStoelhorst, H.J. Stopher, P.Suhaimi Wan ChikSwedlund, A.C. Takforyan, ATesfatsion, Leigh Thbaud, O. Thomas, W. H.THONG-NGAM, C. Toetzer, T.Tong, Hong Lay Torrens, P. Trame, A.Trame, Ann-Marie Trbuil, G.Turner II, B. L. Turner, B.L.Uchman'ski, Januszt Unjee, I.Urban, Christophvan der Veen, A. Veldkamp, A. Velkamp, A. Verburg, P.Verburg, P. H. Vriend, H. J. W., Rand.Waaldijk, F.A. Waddell, Paul Walker, B.Walker, Brian H.Weisbuch, GrardWest, Carla Van Westervelt, JWestervelt, J. D.Westervelt, James D hWestervelt, James D.( White, R.Wilshusen, Richard H.Wyszomirski, Tomaszt Zanon, D. Zellner, M.Zellner, Moira odlpkTj@hg Manson, S. M./ 2000f`Agent-based dynamic spatial simulation of land-use/cover change in the Yucatn peninsula, Mexico^WFourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4)  Banff, Canada lc_abmd]The author presents on-going dissertation research on an Agent-based Dynamic Spatial Simulation (ADSS), used in this paper to project short-term forest-regrowth scenarios in the Yucatn Peninsula, Mexico. A conceptual framework based on land manager decision making in relation to socioeconomic institutions and the environment is mapped onto a model composed of an agent-based model and generalized cellular automata. The ADSS is calibrated and validated with household surveys, archival research, and spatial data including imagery and maps of land-use/cover and biophysical characteristics.nRequiredNGhttp://www.tc.umn.edu/~manson/Resources/Manson_2000_GISEM4_ADSS_www.pdf Steven Mansont 2001<5Simplifying complexity: A review of complexity theoryGeoforum323405-414 2001manson01 Manson, S. M. 2002{Integrated Assessment and Projection of Land-Use and Land- Cover Change in the Southern Yucatan Peninsular Region of Mexico Geography Worchester, MA Clark Manson, S. M. 2004F@The SYPR Integrative Assessment Model: Complexity in Development :3Turner, B.L. Geoghegan, Jacqueline Foster, David R.hbIntegrated Land-Change Science and Tropical Deforestation in the Southern Yucatn: Final Frontiers Oxford Oxford University Pressmanson0481Mathevet, R. Bousquet, F. Le Page, C. Antona, M. 2003Agent-based simulations of interactions between duck population, farming decisions and leasing of hunting rights in the camargue (southern france)Ecological Modelling 165107-126 & Kevin McGarigal Barbara J. Marks 1994XQFRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structuret  Portland, OR VOU.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research StationX 1994"Gen. Tech. Rep. PNW-GTR-351t fragstats lc_vandvReport PNW-GTR-3512,Najlis, R. I. Janssen, M. A. Parker, Dawn C. 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  Santa Barbaraf  CIPEC/CSISS{ CIPEC Collborative Reportc lc_abm0)http://www.csiss.org/maslucc/ABM-LUCC.htm2,Otter, H. S. van der Veen, A. Vriend, H. J. 2001NGAbloom: Location behaviour, spatial patterns, and agent-based modelling<5Journal of Artificial Societies and Social Simulation44 online Dawn C. Parker 1999f_Landscape Outcomes in a Model of Edge-Effect Externalities: A Computational Economics Approacht  Santa Fe, NM Santa Fe Institute July 1999i2,Santa Fe Institute Working Paper 99-07-051 E 99-07-051 E me3 lc_abmJDhttp://www.santafe.edu/sfi/publications/Working-Papers/99-07-051.pdf"!X#zP~} B{ z:~x  HBW. Rand M. Zellner S. E. Page R. Riolo D. G. Brown L. E. Fernandez 2002TNThe Complex Interaction of Agents and Environments: An Example in Urban Sprawl Agent 2002  Chicago, ILv "Argonne National Laboratory http://agent2002.anl.gov/d]Rand, William Brown, Daniel G. Page, Scott E. Riolo, Rick Fernandez, Luis E. Zellner, Moira 2003F@Statistical Validation of Spatial Patterns in Agent-Based ModelsABS 2003 Montpellier, Francep CIRAD' rand03&agent-based modeling power laws4-Reynolds, Robert Timothy A. Kohler Ziad Kobti  2003The Effects of Generalized Reciprocal Exchange on the Resilience of Social Networks: An Example from the Prehispanic Mesa Verde Region60Computational & Mathematical Organization Theory9g3227-254@:Rouchier, J. F. Bousquet, M. Requier-Desjardins M. Antona 2001{A multi-agent model for describing transhumance in North Cameroon: Comparison of different rationality to develop a routinei.(Journal of Economic Dynamics and Control25527-559tRLRouchier, Juliette Bousquet, F. Barreteau, F. O. Page, C. L. Bonnefoy, J.-L. 2001zsMulti-agent modelling and renewable resource issues: the relevance of shared representations for interacting agents "Moss, Scott Davidsson, PaulLFMulti-Agent Based Simulation: Second International Workshop, MABS 2000 Berlin Springer181-197` rouchier01Sasaki, Yuka Box, Paul 2003>8Agent-Based Verification of von Thnen's Location Theory<5Journal of Artificial Societies and Social Simulation62.(http://jasss.soc.surrey.ac.uk/6/2/9.htmlSchelling, Thomas C. 1978$Mircomotives and Macrobehavior.'Fels lectures on public policy analysisi New York  W. W. NortonJ.-C. Souli O. ThbaudIn PressNGModeling fleet response in regulated fisheries: an agent-based approach 4.Journal of Mathematical and Computer Modelling Thbaud, O. Souli, J.-C. 2003leTowards a multiagent simulation model for the analysis of short term fisheries dynamics: a case studyPJ15th Annual Conference of the European Association of Fisheries Economists  Brest, France 14 - 16 May,&http://www.ifremer.fr/eafe/program.htm Torrens, P. 2003,&Automata-based models of urban systems P. A. Longley M. Batty Advanced Spatial Analysis  Redlands, CA  ESRI press 61-81+Torrens, P. Benenson, I.Forthcoming, 2005 "Geographic Automata Systems>7International Journal of Geographic Information SystemsGeographic Automata Systems, cellular automata, multi-agent systems, Geographic Information Science, geosimulation, Geographic Information Systems, Object-Oriented Programming, urban simulation.A novel approach to automata-based modeling for spatial systems is described: geographic automata and Geographic Automata Systems. We detail a framework that takes advantage of the formalism of automata theory and GI Science to unite cellular automata and multi-agent systems techniques, and provides a spatial approach to bottomup modeling of complex geographic systems that are comprised of infrastructure and human objects. The suitability of the framework is also discussed with reference to existing cellular automata and multi-agent systems models used in urban studies. Practical implementation of the framework is illustrated with reference to an object-based urban simulation environment. Torrens, P.In Press2,Geosimulation approaches to traffic modeling 0)P. Stopher K. Button K. Haynes D. Hensher.'Transport Geography and Spatial Systems London Pergamon 81Trame, A. Harper, S. J. Aycrigg, J. Westervelt, Jt 1997nhThe Fort Hood Avian Simulation Model: A Dynamic Model of Ecological Influences on Two Endangered Species Champaign, Ill. *#U.S. Army, Corps of Engineers, CERL 97/88trame9760http://blizzard.gis.uiuc.edu/dsm_FHASM_frame.htm>7Trbuil, G. F. Bousquet C. Baron B. Shinawatra-Ekasingh 2002Collective Creation of Artificial Worlds Can Help Govern Concrete Natural Resource Management Problems: A Northern Thailand ExperienceInternational Symposium: Sustaining Food Security and Managing Natural Resources in Southeast Asia - Challenges for the 21st Century - Chiang Mai, Thailand349-358January 8-11, 2002RL http://www.uni-hohenheim.de/symposium2002/pa_full/Full-Pap-S1-4_Trebuil.pdfD>Trbuil, G. SHINAWATRA-EKASINGH, B. BOUSQUET, F. C. THONG-NGAM 2002rkMulti- Agent Systems Companion Modeling for Integrated Watershed Management: A Northern Thailand Experience X. Jianchu S. MikesellPI3rd International Conference on Montane Mainland Southeast Asia (MMSEA 3) Lijiang, Yunnan, China *#Yunnan Science and Technology Press349-358m2+Verburg, P. H. P. Schot M. Dijst A. Velkamp2 ForthcomingoJC Land-Use Change Modeling: Current Practice and Research Prioritiess GeoJournal verburg03o*#LUCC, modeling methodology,lc_intro$RequiredRKhttp://www.geo.ucl.ac.be/LUCC/MODLUC_Course/PDF/T.%20Veldkamp%20(intro).pdf Verburg, P. Veldkamp, A. FothcomingJCSpecial land-use modeling issue of the International Journal of GISa HBWestervelt, James D. Hannon, Bruce M. Levi, Shaun Harper, Steve J. 1997rkA Dynamic Simulation Model of the Desert Tortoise (Gopherus agassizii) Habitat in the Central Mojave Desert  Champaign, IL *#U.S. Army, Corps of Engineers, CERL 97/102 westervelt976/http://blizzard.gis.uiuc.edu/dsm_TORT_frame.htm&Westervelt, J. D. L. D. Hopkins 199981Modeling mobile individuals in dynamic landscapesr>7International Journal of Geographic Information Systems13191-208Westervelt, James D 2002>8Geographic information systems and agent-based modelling Gimblett, H. R~Integrating Geographic Information Systems and Agent-based Modeling Techniques for Simulating Social and Ecological Processes Oxford Oxford University Press 83-103>8Santa Fe Institute Studies in the Sciences of Complexity westervelt02White, R. Engelen, G. 2000\UHigh-resolution integrated modeling of spatial dynamics of urban and regional systemsy0)Computers, Environment, and Urban Systemse24383-400 Abel2000 Aikman1999 Alberti2000 Alexandridis2002`Q Allerd20020 Amon20020_Angelsen19988B Anh20018 Antona20000 Antona2001j Antona2002j Antona20033 Aquino (d')2002- Aquino (d')2003 Aquino (d')20032 AronovichIn Press Asakawa2002Attonaty20011 Auber2003G Axtell19966 Axtell20000 Aycrigg1997 Babin2003- Bah2003 Bakam19989 Bakam2001f Balan2003. Balmann1997 Balmann2000 Balmann2003} Baron2002 Barreteau2001 Barreteau2001 Barreteau2002  Barreteau20030 Barreteau2003 Barreteau2003 Batty2001$ Batty20030 Becu20030Benenson199881Benenson20040{BenensonForthcoming, 20052BenensonIn Press Berger2001 Berger20024 Berger2002q Berger2002r Berger2002 Berger2002b Bernard2001 Bian2004Q Bieri2002W Bockstael2002Q Bogle2002B Boissau2001 Boissau20035 Boissau2003 Bommel2002F Bommel20044Bonnefoy20011 Bousquet199887Bousquet199868Bousquet20007Bousquet200119Bousquet20018Bousquet2001Bousquet2002}Bousquet2002|~BOUSQUET2002ABousquet20021 Bousquet20038-Bousquet20030KBousquet20030jBousquet2003i;Bousquet2004: Bousset2002 Box2003d Brondizio2002D BrondizioIn Press Brown2002 Brown2003= Brown2004>BrownIn Press?BrownIn PressBrown In Reviewv@ Bruch2004 Carr20000t Caruso2003ACaruso forthcomingBCastella2001A Castella200335Castella20034Q Cherry20022 Chinembri2002\ Chladek2004fCioffi-Revilla2003ACojocaru forthcoming= Collier2004 d'Aquino20033Q Daniel20022  Deadman2002C Deadman2002d Deadman2002 Deadman2003DDeadmanIn Press  Dean2000Deffuant2002$Desyllas2003E Dibble2004'Dieckman2000Dijst Forthcomingn Drazan19955 Dreyfus-Leon2001F Ducrot2004 Duijn2003Duke-Sylvester2002$ Duxbury2003  Engelen1995" Engelen2000G Epstein1996 Epstein2000 Etienne2003H Etienne2003I Etienne2003V Evans2003JEvansIn Press`Evans Under Review F. Bousquet2001E Feldman2004 Fernandez2002 Fernandez2003 Fernandez In ReviewK Feuillette20037 Gautier1998c Geist2003 Gilbert2002ZGimblett2000Y%Gimblett2002NGimblett2002MOGimblett2002NQGimblett2002PRGimblett2003Q\Gimblett2004[S Ginot2002 Gotts2001 Gotts2003GottsIn preparation Grimm1999 Grimm1999Grimm ForthcomingGrimm Forthcoming Gross20028 Guizol20000 Gumerman20008! Hannon19971 Happe2000 Happe2003 Harper1997! Harper19971U Harper2002 Henriot2002 Hesper19833Z Hirst2000\ Hirst2004Hoffmann2003VHoffmann2003U Hogeweg1983 Hopkins1999 Huet20022 Immers2003W Irwin2002Z Itami2000% Itami2002[ Itami2002\ Itami2004 Janssen2000l Janssen2002 Janssen2003 Janssen20032003 Janssen2003 Janssen200303 Janssen2003u Janssen2003u Janssen2003u Janssen2003u Janssen2003nssen2003u Janssen2003n2003u Janssen200303u Janssen2003u Janssen2003u Janssen2003u Janssen2003u Janssen200303u Janssen200303u Janssen200303u Janssen2003u Janssen200303u Janssen2003u Janssen2003u Janssen2003u Janssen2003 -D2aD:JAJ'ODY}@Za8Ql k? #'.2:BKOYat@t@PC`CA K0als aag Dawn editK0 aag Dawn editK0@$  bce?Cu?Cu?Cu???? K0x K0@%@( izOQ QYD @O"ĀV &Ѐ -D2aD:JAJ'ODY}@Za8Qlt@H y @G"L$W& #'.2:BKOYaluy@@а @ B`BAXl k8otated k8ted k8  @$  nf@gDh ?Cu?Cu?Cu???? k8  k8GFs%Fs E j P?P Q QYR @W#D (@W 0H5G= $)16>FsFs k8`dy>{{{>yd5 +{{{{.K Y <%y1GSuSG<p% < YK'&  -q8\Bsb0cX_ R JR]5g]R Jy R>|S0iO YO&JK}E.{ &]H H T r |n {  GfMKwm9719999)F69&bCnt5FEH7& F\n f { { { { { { { | { { c @*@ G]Us?(EEEEH8 IhA OYvI*>W %_:}1F7  PJsx =nG---- 0 ZYb i^dMNFN7RO{ 'EW ## o oRAA(x _WVZU`  *F?Grimm, Volker Tomasz Wyszomirski David Aikman Janusz Uchman'ski 1999PIIndividual-based modelling and ecological theory: synthesis of a workshopEcological Modelling 115 203275282Individual-based modelsTwelve papers featured in a special issue on individual-based modelling in ecology are reviewed in an effort to identify common methodological and theoretical issues. The review focuses on issues related to the question of whether and how individual-based modelling is changing ecological theory. One major hindrance impeding the generation of theory from individual-based models (IBMs) is the fact that IBMs are more or less complex computer simulation models. They are thus hard to develop, hard to communicate, and hard to analyse. Solving this problem requires both software tools which help to implement and communicate IBMs and at least the same effort in analysing the models as is currently put into their development. A new field of application of IBMs is Virtual Ecology, i.e. the comparison of simulated data sets with those obtained by virtual (i.e. simulated) ecologists. This method allows field methods, empirical measures and sampling protocols to be optimised. As far as theoretical issues are concerned, individual variability was by far the most important issue discussed in the papers. Previously most studies concentrated on the mechanisms generating individual variability, but there is now also a growing number of models addressing the consequences of individual variability for population and community dynamics. In order to determine these consequences, a currency is required which allows the model populations to be evaluated. Persistence and other stability properties are proposed as such a unifying currency. The lesson contained in our review is that even with just twelve papers more or less explicitly oriented towards ecological theory, elements of a theory that might emerge from individual-based modelling in the future can already be identified.tRequired Grimm, Volker 1999voTen years of individual-based modelling in ecology: what have we learned and what could we learn in the future?Ecological Modelling 115 2-3{129-148Individual-based models,%Each modeller who builds and analyses an individual-based model learns of course a great deal, but what has ecology as a whole learned from the individual-based models published during the last decade? Answering this question proves extremely difficult as there is no common motivation behind individual-based models. The distinction is introduced between pragmatic motivation, which uses the individual-based approach as a tool without any reference to the theoretical issues which have emerged from the classical state variable approach and paradigmatic motivation, which explicitly refers to theoretical ecology. A mini-review of 50 individual-based animal population models shows that the majority are driven by pragmatic motivation. Most models are very complex and special techniques to cope with this complexity during their analysis are only occasionally applied. It is suggested that in order to orient individual-based modelling more towards general theoretical issues, we need increased explicit reference to theoretical ecology and an advanced strategy for building and analysing individual-based models. To this end, a heuristic list of rules is presented which may help us to advance the practice of individual-based modelling and to learn more general lessons from individual-based modelling in the future than we have during the last decade. The main ideas behind these rules are as follows: (1) Individual-based models usually make more realistic assumptions than state variable models, but it should not be forgotten that the aim of individual-based modelling is not realism but modelling. (2) The individual-based approach is a bottom-up approach which starts with the parts (i.e. individuals) of a system (i.e. population) and then tries to understand how the systems properties emerge from the interaction among these parts. However, bottom-up approaches alone will never lead to theories at the systems level. State variable or top-down approaches are needed to provide an appropriate integrated view, i.e. the relevant questions at the population level.Required(!Grimm, Volker Steven F. Railsback ForthcomingChapter 1: Introduction (!Grimm, Volker Steven F. Railsback,%Individual-based Modeling and Ecology  Princeton, NJ Princeton University PressIndividual-based modelsRequired(!Grimm, Volker Steven F. Railsback ForthcomingChapter 6: Examples (!Grimm, Volker Steven F. Railsback,%Individual-based Modeling and Ecology  Princeton, NJ Princeton University PressIndividual-based modelsdRequired:4Steven J. Harper James D. Westervelt Ann-Marie Trame 2002b[Management application of an agent-based model : control of cowbirds at the landscape scale Gimblett, H. RIntegrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes Oxford University Press$Hoffmann, M H. Kelley T. Evans 2003tnSimulating land-cover change in South-Central Indiana: An agent-based model of deforestation and afforestation  M. A. Janssen\VComplexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches (!Cheltenham, U.K.; Northampton, MAp Edward Elgar PublishersHogeweg, P. Hesper, B. 1983VPThe ontogeny of the interaction structure in bumble bee colonies: A MIRROR model*$Behavioural Ecology and Sociobiology12 271 - 283Individual-based modelsRequired"Elena Irwin Nancy Bockstaeld 2002d]Interacting agents, spatial externalities, and the evolution of residential land use patterns$Journal of Economic Geography0211 31-54 Jan0irwin01lc_statsRequired Hrfdzc~bTimothy A. Kohler 2000.'Dynamics in Human and Primate Societies0 New York and Oxfordl Oxford University Press.(SFI studies in the science of complexity 2000kohler00RKTimothy A. Kohler James Kresl Carla Van West Eric Carr Richard H. Wilshusene 2000Be there then: A modeling approach to settlement determinants and spatial efficiency among late ancestral pueblo populations of the Mesa Verde region, U.S. Southweste ,&Kohler, Timothy A. Gumerman, George J..'Dynamics in Human and Primate Societiess New York and Oxfordl Oxford Univeristy Press0145-178a.(SFI studies in the science of complexity("Michael Kwartler Robert N. Bernard 2001:3CommunityViz: An Integrated Planning Support System ,&Richard K. Brail Richard E. Klosterman^XPlanning Support Systems Integrating Geographic Systems, Models, and Visualization Tools("Lambin, E. F. Geist, H. Lepers, E. 2003 Z>Dynamics of land-use and land-cover change in tropical regions D(Annual Review of Environmental Resources 28 $205-241 T7land use/cover transformation tropical regions lc_intro Lansing, J. Stephenb 1993XRPriests and Programmers: Technologies of Power in the Engineered Landscape of Bali  Princeton, NJ{ Princeton University Press*$Lansing, J. Stephen Kremer, James N. 1993haEmergent Properties of Balinese Water Temple Networks: Coadaptation on a Rugged Fitness Landscapet Chris.G. LangtonArtificial Life III?  Reading, MA Addison-Wesley201-224@9Lim, K. Deadman, P. Moran, E. Brondizio, E. McCracken, S.- 2002d^Agent-based simulations of household decision making and land use change near Altamira, Brazil Gimblett, H. RIntegrating Geographic Information Systems and Agent-Based Modeling Techniques for Understanding Social and Ecological Processes  Oxford, U.K. Oxford University Press@W. Loibl T. Toetzer 2003|vModeling growth and densification processes in suburban regionssimulation of landscape transition with spatial agents*$Environmental Modelling and Software18553563| lc_abmUrban sprawl is an essential environmental issue to be monitored and forecasted in order to think about alternatives that could lead to a more sustainable future development. Thus, the objective of the project presented here is to simulate the past and future transformation of suburban land use patterns in the Vienna Region. (The paper describes some results of the project, STAU-Wien (CitySuburb relations and development in the Vienna Region), was carried out during 20002002). The paper discusses driving forces of suburban growth, and presents a model that simulates polycentric development of suburban systems. The model introduces different settlement growth velocities within the suburban region considering housing area densification and land use change from open space to built up area. In particular, the model takes into account suburban population migration and commercial start ups controlled by regional and local factors (attractiveness/constraints) in the suburban Vienna Region: large and small scale accessibility (traveling time to the core city, access to motorways), land prices, landscape attractiveness, social and commercial services supply, traffic exposure obstacles as well as (land use) zoning constraints. The approach concentrates on a Spatial Agent Model to stimulate regional migration and allocation decisions of households and commercial enterprises aiming in the selection of target municipalities. Land use change will finally be performed by a cellular automaton to decide on densification and land use change. The model has been developed and applied to simulate prior and future landscape transition processes for the suburban region in the surroundings of Vienna, Austria.TMSean Luke Gabriel Catalin Balan Liviu Panait Claudio Cioffi-Revilla Sean PausD 20032,MASON: A Java Multi-Agent Simulation Library Agent 2003  Chicago, IL.D>http://cs.gmu.edu/~eclab/projects/mason/papers/Agent2003.6.pdf Lynam, T. 2002~wScientific measurements and villagers' knowledge: an integrative multi-agent model from the semi-arid areas of Zimbabwe' Janssen, M. A.*#Complexity and Ecosystem Management Northampton, MA  Edward Elgar188-217lynam02f_Lynam, T. Bousquet, F. Aquino (d'), P. Barreteau, F. O. LePage, C. Chinembri, F. Mombeshora, B.  2002jcAdapting Science to Adaptive Managers: Spidergrams, Belief Models, and Multi-agent Systems ModelingConservation Ecology52Participatory ABM Two case studies are presented in which models were used as focal tools in problems associated with common-pool resource management in developing countries. In the first case study, based in Zimbabwe, Bayesian or Belief Networks were used in a project designed to enhance the adaptive management capacity of a community in a semiarid rangeland system. In the second case study, based in Senegal, multi-agent systems models were used in the context of role plays to communicate research findings to a community, as well as to explore policies for improved management of rangelands and arable lands over which herders and farmers were in conflict. The paper provides examples of the use of computer-based modeling with stakeholders who had limited experience with computer systems and numerical analyses. The paper closes with a brief discussion of the major lessons learned from the two independent case studies. Perhaps the most important lesson was the development of a common understanding of a problem through the development of the models with key stakeholders. A second key lesson was the need for research to be adaptive if it were to benefit adaptive managers. Both case study situations required significant changes in project orientation as stakeholder needs were defined. Both case studies recognized the key role that research, and particularly the development of models, played in bring different actors together to formulate improved management strategies or policies. Participatory engagement with stakeholders is a time-consuming and relatively costly process in which, in the case studies, most of the costs were born by the research projects themselves. We raise the concern that these activities may not be widely replicable if such costs are not reduced or born by the stakeholders themselves.81http://www.ecologyandsociety.org/vol5/iss2/art24/ Lynam, T. 2003voComplex and useful but certainly wrong: A multi-agent agro-ecosystem model from the semi-arid areas of ZimbabweF  M. A. Janssen\VComplexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches (!Cheltenham, U.K.; Northampton, MAp Edward Elgar Publishersbes  Oxford, U.K. Oxford University Press@TMSean Luke Gabriel Catalin Balan Liviu Panait Claudio Cioffi-Revilla Sean PausD 20032,MASON: A Java Multi-Agent Simulation Library Agent 2003  Chicago, IL.D>http://cs.gmu.edu/~eclab/projects/mason/papers/Agent2003.6.pdf Lynam, T. 2002~wScientific measurements and villagers' knowledge: an integrative multi-agent model from the semi-arid areas of Zimbabwe' Janssen, M. A.*#Complexity and Ecosystem Management Northampton, MA  Edward Elgar188-217lynam02f_Lynam, T. Bousquet, F. Aquino (d'), P. Barreteau, F. O. LePage, C. Chinembri, F. Mombeshora, B.  2002jcAdapting Science to Adaptive Managers: Spidergrams, Belief Models, and Multi-agent Systems ModelingConservation Ecology52Participatory ABM Two case studies are presented in which models were used as focal tools in problems associated with common-pool resource management in developing countries. In the first case study, based in Zimbabwe, Bayesian or Belief Networks were used in a project designed to enhance the adaptive management capacity of a community in a semiarid rangeland system. In the second case study, based in Senegal, multi-agent systems models were used in the context of role plays to communicate research findings to a community, as well as to explore policies for improved management of rangelands and arable lands over which herders and farmers were in conflict. The paper provides examples of the use of computer-based modeling with stakeholders who had limited experience with computer systems and numerical analyses. The paper closes with a brief discussion of the major lessons learned from the two independent case studies. Perhaps the most important lesson was the development of a common understanding of a problem through the development of the models with key stakeholders. A second key lesson was the need for research to be adaptive if it were to benefit adaptive managers. Both case study situations required significant changes in project orientation as stakeholder needs were defined. Both case studies recognized the key role that research, and particularly the development of models, played in bring diff