Agent-Based Modelling

Introduction

Agent-based models (ABMs) are computer simulations based on object-oriented programming, in which discrete ‘agents’ (objects) interact in real time with each other and their environment according to certain rules. Agents can represent individuals, households, firms, governments or even land types, pathogens, livestock, power grids etc. ABMs still use mathematics, but the mathematics is embedded in the rules governing agents’ properties, behaviours and interactions, instead of governing and restricting the entire system and requiring it to converge to an equilibrium. ABMs permit the economic, social, legal, political, geographic, environmental, epidemiological and ethical dimensions of development policies to be integrated to a far greater degree than is possible with purely mathematical models. Agent-based modelling using object-oriented code libraries is also ideally suited to the development of theory based on taxonomical classification of different system components and their interactions.

ABMs are ideally suited to acting as a bridge between disciplines. They have opened up a new interdisciplinary research frontier spanning: anthropology, climate change, combat and conflict, development and natural resource management, ecology, economics, emergency responses, energy markets, epidemiology, finance, geography, innovation and organisation theory, learning, migration, medicine, operations research, peacekeeping, political science, sociology, terrorism, transport, as well as more general works and active research on methodological issues such as ABM design and verification and validation of ABM results.

Dr Simon Angus and I taught a new unit on ‘Integrated Economic Modelling’ at Monash University’s Clayton Campus in 2nd Semester (July to November) 2010, 2011 and 2012. Behrooz-Hassani-M developed and ran the tutorials on NetLogo. Here is the unit guide and here are some student models from their major project from 2010. This unit is not being taught in 2013.

Here is a short presentation I gave to a CSIRO Complex Systems Science workshop on 6 May 2009 on Evaluating Modelling Frameworks.

Books
Papers & Chapters
Quotes
Links

Books

Agent-Based Modelling

Axelrod, R., (1997) The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton University Press, Princeton NJ, xiv+232 pp.

Batten, D.F., (2000) Discovering Artificial Economics: How Agents Learn and Economies Evolve, Westview Press, Boulder and Oxford, xxi + 314 pp.

Batty, M., (2005) Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals, MIT Press, Cambridge, MA & London, xxiii + 565 pp.

Deguchi, H., (2004) Economics as an Agent-Based Complex System, Springer-Verlag, Tokyo, Berlin, Heidelberg & New York, xiii+261 pp.

Delli Gatti, D., Gaffeo, E., Gallegati, M., Giulioni, G. and Palestrini, A., (2008) Emergent Macroeconomics: An Agent-Based Approach to Business Fluctuations, Series ed. Faggini, M., Gallegati, M. and Kirman, A.P.; New Economic Windows; Springer, Milan, Berlin, Heidelberg & New York, xi + 114 pp.

Delli Gatti, D., Desiderio, S., Gaffeo, E., Cirillo, P. and Gallegati, M., (2011) Macroeconomics from the Bottom-up, New Economic Windows; Springer-Verlag Italia, Milan, Dordrecht, Heidelberg, London & New York, xii + 122 pp.

Epstein, J.M., (2006) Generative Social Science: Studies in Agent-Based Computational Modeling, Princeton University Press, Princeton, NJ, xx + 356 pp.

Epstein, J.M. and Axtell, R., (1996) Growing Artificial Societies: Social Sciences from the Bottom Up, MIT Press, Cambridge, MA, xv + 208 pp.

Gilbert, N., (2008) Agent-Based Models, Quantitative Applications in the Social Sciences No. 153; SAGE Publications, Los Angeles & London, xiii + 98 pp.

Gilbert, N. and Troitzsch, K.G., (2005) Simulation for the Social Scientist, 2nd Edition; Open University Press, Maidenhead & New York, xi+295 pp.

Hamill, L. and Gilbert, G.N., (2015) Agent-Based Modelling in Economics, John Wiley & Sons, Hoboken, NJ, 256 pp.

Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M. (Eds.), (2012) Agent-Based Models of Geographical Systems, Springer Business+Science Media, Dordrecht, Heidelberg, London & New York, viii + 759 pp.

Laver, M. and Sergenti, E., (2012) Party Competition: An Agent-Based Model, Princeton Studies in Complexity; Princeton University Press, Princeton NJ, xi + 278 pp.

Leombruni, R. and Richiardi, M. (Eds.), (2004) Industry and Labor Dynamics: The Agent-Based Computational Approach, Proceedings of the Wild@Ace2003 Workshop, Torino, Italy, 3-4 October, 2003; World Scientific, Singapore, Hackensack, NJ & London, xxiii + 405 pp.

Miller, J.H. and Page, S.E., (2007) Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press, Princeton, NJ & Oxford, xix + 263 pp.

North, M.J. and Macal, C.M., (2007) Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation, Oxford University Press, Oxford & New York, xi + 313 pp.

Page, S.E., (2011) Diversity and Complexity, Primers in Complex Systems; Princeton University Press, Princeton NJ & Oxford, x + 291 pp.

Perez, P. and Batten, D.F. (Eds.), (2006) Complex Science for a Complex World: Exploring Human Ecosystems with Agents, ANU E Press, Canberra, xv + 334 pp.

Railsback, S.F. and Grimm, V., (2012) Agent-Based and Individual-Based Modeling: A Practical Introduction, Princeton University Press, Princeton NJ, xviii + 329 pp.

Šalomon, T., (2011) Design of Agent-Based Models: Developing Computer Simulations for Better Understanding of Social Processes, Thomáš Bruckner, Řepin – Živonín, Czech Republic, ix + 208 pp.

Sawyer, R.K., (2005) Social Emergence: Societies as Complex Systems, Cambridge University Press, Cambridge, ix + 276 pp.

Squazzoni, F., (2012) Agent-Based Computational Sociology, John Wiley & Sons, Chichester UK, xvi + 238 pp.

Tesfatsion, L. and Judd, K.L. (Eds.), (2006) Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics, North-Holland, Amsterdam, Boston & London, xxx + pp. 829-1660 pp.

Java

To start with, I knew nothing about Java and had virtually no programming experience. I hunted around for good introductory books and settled on Barry Burd’s two introductory books in the ‘Dummies’ series. Just get past the titles – the books are great, and if you have no programming experience, the Beginning Programming one is excellent. These are the most recent editions at the time of writing:

Burd, B., (2014) Beginning Programming with Java for Dummies, 4th Revised Edition; Wiley Publishing, Hoboken, NL, 480 pp.

Burd, B., (2017) Java for Dummies, 7th Revised Edition; Wiley Publishing, Hoboken, NL, 504 pp.

An excellent, more comprehensive Java textbook is:

Horstmann, C., (2010) Big Java, 4th Edition; John Wiley & Sons, Hoboken, NJ.

Other useful Java books include:

Arnold, K., Gosling, J. and Holmes, D., (2006) The Java Programming Language, 4th Edition; Addison-Wesley for Sun Microsystems, Upper Saddle River, NJ, xxviii + 891 pp.

Eckel, B., (2006) Thinking in Java, 4th Edition; Prentice Hall, Upper Saddle River, NJ, 1482 pp.

Flanagan, D., (2005) Java in a Nutshell: A Desktop Quick Reference, 5th Edition; O’Reilly Media, Sebastopol, CA, xxiv + 1225 pp.

Mak, R., (2003) Java Number Cruncher: The Java programmer’s Guide to Numerical Computing, Prentice Hall, Upper Saddle River, NJ, xi + 464 pp.

McLaughlin, B.D. and Edelson, J., (2007) Java & XML, 3rd Edition; O’Reilly Media, Sebastopol, CA, xii + 465 pp.

Sierra, K. and Bates, B., (2005) Head First Java, 2nd Edition; O’Reilly, Sebastopol, CA, xxxii + 688 pp.

Eclipse

You can program in Java with a simple text editor, but using an Integrated Development Environment (IDE), makes life so much easier. Eclipse is arguably one the best IDE’s. A good quick introduction to the main features of Eclipse is:

Burd, B., (2005) Eclipse for Dummies, Wiley Publishing, Hoboken, NL, xiv + 346 pp.

Unified Modeling Language (UML) & Object-Oriented Design

For an excellent introduction to object-oriented concepts, for example if you trained on older procedural languages, try:

Weisfeld, M., (2004) The Object-Oriented Thought Process, 2nd Edition; Sams Publishing Developer’s Library, Indianapolis, xi + 271 pp.

Good books on UML include:

Bennett, S., Skelton, J. and Lunn, K., (2005) UML, 2nd Edition; Schaum’s Outline Series; McGraw Hill, New York & London, ix + 398 pp.

Chonoles, M.J. and Schardt, J.A., (2003) UML 2 for Dummies, Wiley Publishing, New York, xvi + 412 pp.

Larman, C., (2004) Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and Iterative Development, 3rd Edition; Prentice Hall PTR, Upper Saddle River, NJ, xxv + 703 pp.

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Papers & Chapters

General

Aumann, C.A., (2007) “A Methodology for Developing Simulation Models of Complex Systems”, Ecological Modelling, Vol. 202, No. 3-4, April, pp. 385-396.

Axelrod, R., (2006) “Agent-Based Modeling as a Bridge Between Disciplines”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1565-1584.

Axelrod, R. and Tesfatsion, L., (2006) “A Guide for Newcomers to Agent-Based Modeling in the Social Sciences“, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1647-1659.

Bainbridge, W.S., (2007) “The Scientific Research Potential of Virtual Worlds”, Science, Vol. 317, No. 5837, 27 July, pp. 472-476.
[ABMs overlap with some interesting work being undertaken on massive online roleplaying games]

Bonabeau, E., (2002) “Agent-Based Modeling: Methods and Techniques for Simulating Human Systems”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, Supplement 3, 14 May, pp. 7280-7287.

Dawid, H., (2007) “Evolutionary Game Dynamics and the Analysis of Agent-Based Imitation Models: The Long Run, the Medium Run and the Importance of Global Analysis”, Journal of Economic Dynamics and Control, Vol. 31, No. 6, June, pp. 2108-2133.

Epstein, J.M., (2008) “Why Model?Journal of Artificial Societies and Social Simulation, Vol. 11, No. 4, October, 5 pp.

Heath, B., Hill, R. and Ciarallo, F., (2009) “A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)“, Journal of Artificial Societies and Social Simulation, Vol. 12, No. 4, October, 42 pp.

Huet, S. and Deffuant, G., (2008) “Differential Equation Models Derived from an Individual-Based Model Can Help to Understand Emergent Effects“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 2, March, 16 pp.

Janssen, M.A. and Ostrom, E., (2006) “Empirically Based, Agent-Based Models“, Ecology and Society, Vol. 11, No. 2, 13 pp.

Janssen, M.A., Alessa, L.N.i., Barton, M., Bergin, S. and Lee, A., (2008) “Towards a Community Framework for Agent-Based Modelling“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 2, March, 13 pp.

Kendrick, D.A., (2007) “Teaching Computational Economics to Graduate Students”, Computational Economics, Vol. 30, No. 4, November, pp. 381-391.

Lysenko, M. and D’Souza, R.M., (2008) “A Framework for Megascale Agent Based Model Simulations on Graphics Processing Units“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 4, October, 17 pp.

Ma, T., Nakamori, Y. and Huang, W., (2006) “An Agent-Based Approach for Predictions Based on Multi-Dimensional Complex Data”, Information Sciences, Vol. 176, No. 9, 8 May, pp. 1156-1174.

Nikolai, C. and Madey, G., (2009) “Tools of the Trade: A Survey of Various Agent Based Modeling Platforms“, Journal of Artificial Societies and Social Simulation, Vol. 12, No. 2, March, 37 pp.

Polhill, J.G. and Edmonds, B., (2007) “Open Access for Social Simulation“, Journal of Artificial Societies and Social Simulation, Vol. 10, No. 3, June, pp. 16.

Railsback, S., Lytinen, S. and Jackson, S., (2006) “Agent-Based Simulation Platforms: Review and Development Recommendations”, Simulation, Vol. 82, No. 9, September, pp. 609-623.

Rauch, J., (2002) “Seeing Around Corners”, The Atlantic Monthly, Vol. 289, No. 4, April, pp. 35-48.

Ryoke, M. and Nakamori, Y., (2005) “Agent-Based Approach to Complex Systems Modeling”, European Journal of Operational Research, Vol. 166, No. 3, November, pp. 717-725.

Triebig, C. and Klügl, F., (2009) “Elements of a Documentation Framework for Agent-Based Simulation Models“, Cybernetics and Systems, Vol. 40, No. 5, pp. 441-474.

The Economist, (2009) “Model Behaviour“, The Economist, Vol. 390, No. 8621, Technology Quarterly, 7 March, pp. 24-25.

Zyda, M., (2005) “From Visual Simulation to Virtual Reality to Games”, IEEE Computer, Vol. 38, No. 9, September, pp. 25-32. Presentation here.

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Anthropology

Axtell, R.L., Epstein, J.M., Dean, J.S., Gumerman, G.J., Swedlund, A.C., Harburger, J., Chakravarty, S., Hammond, R., Parker, J. and Parker, M., (2002) “Population Growth and Collapse in a Multiagent Model of the Kayenta Anasazi in Long House Valley”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, No. 3, 14 May, pp. 7275-7279.

Bousquet, F., Le Page, C., Bakam, I. and Takforyan, A., (2001) “Multiagent Simulations of Hunting Wild Meat in a Village in Eastern Cameroon”, Ecological Modelling, Vol. 138, No. 1-3, March, pp. 331-346.

Diamond, J.M., (2002) “Life with the Artificial Anasazi”, Nature, Vol. 419, No. 6907, 10 October, pp. 567-569.

Janssen, M., (2009) “Understanding Artificial Anasazi“, Journal of Artificial Societies and Social Simulation, Vol. 12, No. 4, October, 17 pp.

Kohler, T.A., (2005) “Simulating Ancient Societies”, Scientific American, Vol. 293, No. 1, July, pp. 76-84.

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Climate Change

Angus, S.D., Parris, B.W. and Hassani-M., B., (2009) “Climate Change Impacts and Adaptation in Bangladesh: An Agent-Based Approach“, In 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation ed. Anderssen, R.S., Braddock, R.D. and Newham, L.T.H.; Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, July, pp. 2720-2726.

Janssen, M.A. and de Vries, H.J.M., (1998) “The Battle of Perspectives: A Multi-Agent Model with Adaptive Responses to Climate Change”, Ecological Economics, Vol. 26, No. 1, July, pp. 43-65.

Moss, S., Pahl-Wostl, C. and Downing, T.E., (2001) “Agent-Based Integrated Assessment Modeling: The Example of Climate Change”, Integrated Assessment, Vol. 2, No. 1, March, pp. 17-30.

Patt, A. and Siebenhüner, B., (2005) “Agent Based Modeling and Adaptation to Climate Change”, Vierteljahrshefte zur Wirtschaftsforschung, Vol. 74, No. 2, pp. 310-320.

Ziervogel, G., Bithell, M., Washington, R. and Downing, T., (2005) “Agent-Based Social Simulation: A Method for Assessing the Impact of Seasonal Climate Forecast Applications Among Smallholder Farmers”, Agricultural Systems, Vol. 83, No. 1, January, pp. 1-26.

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Combat and Conflict

Bennett, D.S., (2008) “Governments, Civilians, and the Evolution of Insurgency: Modeling the Early Dynamics of Insurgencies“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 4, October, 23 pp.

Bhavnani, R., Miodownik, D. and Nart, J., (2008) “REsCape: An Agent-Based Framework for Modeling Resources, Ethnicity, and Conflict“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 2, March, 14 pp.

Chaturvedi, A.R., Dolk, D., Chaturvedi, R., Mulpuri, M., Lengacher, D., Mellema, S., Poddar, P., Foong, C. and Armstrong, B., (2005) “Understanding Insurgency by Using Agent-Based Computational Experimentation: Case Study of Indonesia“, In Proceedings of the Agent 2005 Conference on Generative Social Processes, Models, and Mechanisms ed. Macal, C.M., North, M.J. and Sallach, D.; ANL/DIS-06-5, Co-sponsored by Argonne National Laboratory and The University of Chicago, October 13-15, pp. 781-799.

Hassani-M, B. and Parris, B.W., (2009) “Designing Adaptive Artificial Agents for an Economic Production and Conflict Model“, In Artificial Life: Borrowing from Biology; Lecture Notes in Computer Science, Vol. 5865 ed. Korb, K., Randall, M. and Hendtlass, T.; Springer, Berlin & Heidelberg, pp. 179-190.

Ilachinski, A., (2004) Artificial War: Multiagent-Based Simulation of Combat, World Scientific Publishing Company, Singapore, 784 pp.

Koehler, M.T.K., Barry, P.S. and Meyer, T.E., (2006) “Sending Agents to War“, In Proceedings of the Agent 2006 Conference on Social Agents: Results and Prospects ed. Sallach, D., Macal, C.M. and North, M.J.; ANL/DIS-06-7, Co-sponsored by Argonne National Laboratory and The University of Chicago, September 21-23, pp. 245-253.

Nakai, Y. and Muto, M., (2008) “Emergence and Collapse of Peace with Friend Selection Strategies“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 3, June, 32 pp.

Reuss, G., Stone, G., Schutzmeister, S., Stephens, S. and Ross-Witkowski, C., (2006) “MORS Workshop: Agent-Based Models and Other Analytic Tools in Support of Stability Operations“, Final report of a workshop held in McLean, Virginia from 25-27 October 2005, Alexandria, Virginia, Military Operations Research Society, 15 February, 47 pp.

Vasconcelos, W., Kollingbaum, M. and Norman, T., (2009) “Normative Conflict Resolution in Multi-Agent Systems”, Autonomous Agents and Multi-Agent Systems, Vol. 19, No. 2, October, pp. 124-152.

Wheeler, S., (2005) “It Pays to Be Popular: A Study of Civilian Assistance and Guerilla Warfare“, Journal of Artificial Societies and Social Simulation, Vol. 8, No. 4, October, pp. 13.

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Development and Natural Resource Management

Acosta-Michlik, L. and Espaldon, V., (2008) “Assessing Vulnerability of Selected Farming Communities in the Philippines based on a Behavioural Model of Agent’s Adaptation to Global Environmental Change”, Global Environmental Change, Vol. 18, No. 4, October, pp. 554-563.

Barreteau, O., (2003) “Our Companion Modelling Approach“, Journal of Artificial Societies and Social Simulation, Vol. 6, No. 1, March, 6 pp.

Barreteau, O. and Bousquet, F., (2000) “SHADOC: A Multiagent Model to Tackle Viability of Irrigated Systems”, Annals of Operations Research, Vol. 94, pp. 139-162.

Barreteau, O., Bousquet, F. and Attonaty, J.-M., (2001) “Role-Playing Games for Opening the Black Box of Multi-Agent Systems: Method and Lessons of its Application to Senegal River Valley Irrigated Systems“, Journal of Artificial Societies and Social Simulation, Vol. 4, No. 2, March, pp. 18.

Becu, N., Bousquet, F., Barreteau, O., Perez, P. and Walker, A., (2003) “A Methodology for Eliciting and Modelling Stakeholders’ Representations with Agent Based Modelling”, In Multi-Agent Based Simulation III, Revised papers from the 4th International Workshop (MABS 2003), Melbourne, Australia, July 14, 2003, Lecture Notes in Computer Science Vol. 2927 ed. Hales, D., Edmonds, B. and Norling, E.; Springer-Verlag, Berlin, pp. 131-148.

Berger, T., Schreinemachers, P. and Woelcke, J., (2006) “Multi-Agent Simulation for the Targeting of Development Policies in Less-Favored Areas”, Agricultural Systems, Vol. 88, No. 1, April, pp. 28-43.

Bithell, M. and Brasington, J., (2009) “Coupling Agent-Based Models of Subsistence Farming with Individual-Based Forest Models and Dynamic Models of Water Distribution”, Environmental Modelling & Software, Vol. 24, No. 2, February, pp. 173-190.

Boulanger, P.-M. and Bréchet, T., (2005) “Models for Policy-Making in Sustainable Development: The State of the Art and Perspectives for Research”, Ecological Economics, Vol. 55, No. 3, 15 November, pp. 337-350.

Dionnet, M., Kuper, M., Hammani, A. and Garin, P., (2008) “Combining Role-playing Games and Policy Simulation Exercises: An Experience with Moroccan Smallholder Farmers”, Simulation & Gaming, Vol. 39, No. 4, December, pp. 498-514.

Dray, A., Perez, P., Jones, N., Le Page, C., D’Aquino, P. and Auatabu, T., (2006) “The AtollGame Experience: From Knowledge Engineering to a Computer-Assisted Role Playing Game“, Journal of Artificial Societies and Social Simulation, Vol. 9, No. 1, January, pp. 10.

Dray, A., Perez, P., Le Page, C., D’Aquino, P. and White, I., (2006) “AtollGame: A Companion Modelling Experience in the Pacific“, In Complex Science for a Complex World: Exploring Human Ecosystems with Agents ed. Perez, P. and Batten, D.F.; ANU E Press, Canberra, pp. 255-282.

Galán, J.M., López-Paredes, A. and del Olmo, R., (2009) “An Agent-Based Model for Domestic Water Management in Valladolid Metropolitan Area“, Water Resources Research, Vol. 45, W05401, 2 May, pp. 17.

Gurung, T.R., Bousquet, F. and Trébuil, G., (2006) “Companion Modeling, Conflict Resolution, and Institution Building: Sharing Irrigation Water in the Lingmuteychu Watershed, Bhutan“, Ecology and Society, Vol. 11, No. 2, 49 pp.

Guyot, P. and Honiden, S., (2006) “Agent-Based Participatory Simulations: Merging Multi-Agent Systems and Role-Playing Games“, Journal of Artificial Societies and Social Simulation, Vol. 9, No. 4, 31 October, 15 pp.

Hassani-Mahmooei, B. and Parris, B.W., (2013) “Resource Scarcity, Effort Allocation and Environmental Security: An Agent-Based Theoretical Approach“, Economic Modelling, Vol. 30, January, pp. 183-192.

Little, L.R. and McDonald, A.D., (2007) “Simulations of Agents in Social Networks Harvesting a Resource”, Ecological Modelling, Vol. 204, No. 3-4, 16 June, pp. 379-386.

Manson, S.M. and Evans, T., (2007) “Agent-based Modeling of Deforestation in Southern Yucatan, Mexico, and Reforestation in the Midwest United States”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 104, No. 52, 26 December, pp. 20678-20683.

Mathey, A.-H., Krcmar, E., Dragicevic, S. and Vertinsky, I., (2008) “An Object-Oriented Cellular Automata Model for Forest Planning Problems”, Ecological Modelling, Vol. 212, No. 3-4, 10 April, pp. 359-371.

Moglia, M., Perez, P. and Burn, S., (2010) “Modelling an Urban Water System on the Edge of Chaos”, Environmental Modelling & Software, Vol. 25, No. 12, December, pp. 1528-1538.

Robinson, D.T., Brown, D.G., Parker, D.C., Schreinemachers, P., Janssen, M.A., Huigen, M., Wittmer, H., Gotts, N., Promburom, P., Irwin, E., Berger, T., Gatzweiler, F. and Barnaud, C., (2007) “Comparison of Empirical Methods for Building Agent-Based Models in Land Use Science”, Journal of Land Use Science, Vol. 2, No. 1, March, pp. 31 – 55.

Schreinemachers, P., Berger, T. and Aune, J.B., (2007) “Simulating Soil Fertility and Poverty Dynamics in Uganda: A Bio-Economic Multi-Agent Systems Approach”, Ecological Economics, Vol. 64, No. 2, 15 December, pp. 387-401.

Smajgl, A., (2007) “Modelling Evolving Rules for the Use of Common Pool Resources in an Agent-Based Model“, Interdisciplinary Description of Complex Systems, Vol. 5, No. 2, pp. 56-80.

Smajgl, A., Heckbert, S., Ward, J. and Straton, A., (2009) “Simulating Impacts of Water Trading in an Institutional Perspective”, Environmental Modelling & Software, Vol. 24, No. 2, February, pp. 191-201.

Valbuena, D., Verburg, P.H. and Bregt, A.K., (2008) “A Method to Define a Typology for Agent-Based Analysis in Regional Land-Use Research”, Agriculture, Ecosystems & Environment, Vol. 128, No. 1-2, October, pp. 27-36.

van Hofwegen, G., Becx, G.A., van den Broek, J.A. and Koning, N.B.J., (2007) “Unraveling the Unsustainability Spiral in Subsaharan Africa: An Agent-Based Modelling Approach“, Interdisciplinary Description of Complex Systems, Vol. 5, No. 2, pp. 112-137.

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Ecology

Breckling, B., Middelhoff, U. and Reuter, H., (2006) “Individual-Based Models as Tools for Ecological Theory and Application: Understanding the Emergence of Organisational Properties in Ecological Systems”, Ecological Modelling, Vol. 194, No. 1-3, March, pp. 102-113.

Conner, M.M., Ebinger, M.R. and Knowlton, F.F., (2008) “Evaluating Coyote Management Strategies Using a Spatially Explicit, Individual-Based, Socially Structured Population Model”, Ecological Modelling, Vol. 219, No. 1-2, 24 November, pp. 234-247.

Green, D. and Sadedin, S., (2005) “Interactions Matter – Complexity in Landscapes and Ecosystems”, Ecological Complexity, Vol. 2, No. 2, pp. 117-130.

Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W.M., Railsback, S.F., Thulke, H.-H., Weiner, J., Wiegand, T. and DeAngelis, D.L., (2005) “Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology”, Science, Vol. 310, No. 5750, 11 November, pp. 987-991.

Janssen, M.A. and Ostrom, E., (2006) “Governing Social-Ecological Systems”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1465-1509.

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Economics

Arthur, W.B., (2006) “Out-of-Equilibrium Economics and Agent-Based Modeling”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1551-1564.

Atkins, K., Marathe, A. and Barrett, C., (2007) “A Computational Approach to Modeling Commodity Markets”, Computational Economics, Vol. 30, No. 2, September, pp. 125-142.

Barnaud, C., Bousquet, F. and Trebuil, G., (2008) “Multi-Agent Simulations to Explore Rules for Rural Credit in a Highland Farming Community of Northern Thailand”, Ecological Economics, Vol. 66, No. 4, 15 July, pp. 615-627.

Buchanan, M., (2009) “Meltdown Modelling“, Nature, Vol. 460, No. 7256, 6 August, pp. 680-682.

Caiani, A., Godin, A., Caverzasi, E., Gallegati, M., Kinsella, S. and Stiglitz, J.E., (2016) “Agent Based-Stock Flow Consistent Macroeconomics: Towards a Benchmark Model“, Journal of Economic Dynamics and Control, Vol. 69, August, pp. 375-408.

Chaturvedi, A., Mehta, S., Dolk, D. and Ayer, R., (2005) “Agent-Based Simulation for Computational Experimentation: Developing an Artificial Labor Market”, European Journal of Operational Research, Vol. 166, No. 3, November, pp. 694-716.

Chen, S.-H., (2003) “Agent-Based Computational Macroeconomics: A Survey”, In Meeting the Challenge of Social Problems via Agent-Based Simulation: Post Proceedings of the Second International Workshop on Agent-Based Approaches in Economic and Social Complex Systems ed. Terano, T., Dehuchi, H. and Takadama, K.; Springer-Verlag, Heidelberg & New York, pp. 141-170.

Chen, S.-H., (2005) “Computational Intelligence in Economics and Finance: Carrying on the Legacy of Herbert Simon”, Information Sciences, Vol. 170, No. 1, February, pp. 121-131.

Chen, S.-H., (2005) “Trends in Agent-Based Computational Modeling of Macroeconomics”, New Generation Computing, Vol. 23, No. 1, pp. 3-11.

Deissenberg, C., van der Hoog, S. and Dawid, H., (2008) “EURACE: A Massively Parallel Agent-Based Model of the European Economy”, Applied Mathematics and Computation, Vol. 204, No. 2, 15 October, pp. 541-552.

Dosi, G., Fagiolo, G. and Roventini, A., (2010) “Schumpeter Meeting Keynes: A Policy-Friendly Model of Endogenous Growth and Business Cycles”, Journal of Economic Dynamics and Control, Vol. 34, No. 9, September, pp. 1748-1767.

Edmonds, B. and Hales, D., (2004) “When and Why Does Haggling Occur? Some Suggestions from a Qualitative but Computational Simulation of Negotiation“, Journal of Artificial Societies and Social Simulation, Vol. 7, No. 2, March, pp. 33.

Farmer, J.D. and Foley, D., (2009) “The Economy Needs Agent-Based Modelling“, Nature, Vol. 460, No. 7256, 6 August, pp. 685-686.

Gibson, B., (2007) “A Multi-Agent Systems Approach to Microeconomic Foundations of Macro“, Working Paper 2007-10, Amherst, MA, Department of Economics, University of Massachusetts, 23 pp.

Hassani-Mahmooei, B. and Parris, B., (2014) “Dynamics of Effort Allocation and Evolution of Trust: An Agent-Based Model“, Computational and Mathematical Organization Theory, Vol. 20, No. 2, June, pp. 133-154.

Higgins, A., Thorburn, P., Archer, A. and Jakku, E., (2007) “Opportunities for Value Chain Research in Sugar Industries”, Agricultural Systems, Vol. 94, No. 3, June, pp. 611-621.

Hoekstra, R.C., van Arkel, H. and Leurs, B., (2007) “Modeling Local Monetary Flows in Poor Regions: A Research Setup to Simulate the Multiplier Effect in Local Economies”, Interdisciplinary Description of Complex Systems, Vol. 5, No. 2, pp. 138-150.

Holland, J.H. and Miller, J.H., (1991) “Artificial Adaptive Agents in Economic Theory”, American Economic Review, Vol. 81, No. 2, May, pp. 365-371.

Howitt, P., (2006) “Coordination Issues in Long-Run Growth”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1605-1624.

Judd, K.L., (2006) “Computationally Intensive Analyses in Economics”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 881-893.

Kirman, A.P. and Vriend, N.J., (2001) “Evolving Market Structure: An ACE Model of Price Dispersion and Loyalty”, Journal of Economic Dynamics and Control, Vol. 25, No. 3-4, March, pp. 459-502.

Lane, D.A., (1993) “Artificial Worlds and Economics, Part I”, Journal of Evolutionary Economics, Vol. 3, No. 2, May, pp. 89-107.

Lane, D.A., (1993) “Artificial Worlds and Economics, Part II”, Journal of Evolutionary Economics, Vol. 3, No. 3, August, pp. 177-197.

Leijonhufvud, A., (2006) “Agent-Based Macro”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1625-1637.

Marks, R., (2006) “Market Design Using Agent-Based Models”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1339-1380.

Neugart, M., (2008) “Labor Market Policy Evaluation with ACE”, Journal of Economic Behavior & Organization, Vol. 67, No. 2, August, pp. 418-430.

Parris, B.W., (2005) “An Agent-Based Approach to Value Theory and Wealth Distribution in Economics“, In MODSIM 2005 International Congress on Modelling and Simulation ed. Zerger, A. and Argent, R.M.; Modelling and Simulation Society of Australia and New Zealand, 12-15 December 2005, Melbourne, pp. 1077-1083.

Tesfatsion, L., (1997) “How Economists Can Get ALife“, In The Economy as an Evolving Complex System II ed. Arthur, W.B., Durlauf, S.N. and Lane, D.A.; Westview Press, Boulder, pp. 533-564.

Tesfatsion, L., (2001) “Structure, Behavior, and Market Power in an Evolutionary Labor Market with Adaptive Search”, Journal of Economic Dynamics & Control, Vol. 25, No. 3-4, March, pp. 419-457.

Tesfatsion, L., (2002) “Agent-Based Computational Economics: Growing Economies From the Bottom Up”, Artificial Life, Vol. 8, No. 1, pp. 55-82.

Tesfatsion, L., (2002) “Economic Agents and Markets as Emergent Phenomena”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, Supplement 3, December, pp. 7191-7192.

Tesfatsion, L., (2003) “Agent-Based Computational Economics: Modeling Economies as Complex Adaptive Systems”, Information Sciences, February, Vol. 149 263-269 pp.

Tesfatsion, L., (2006) “Agent Based Computational Economics: A Constructive Approach to Economic Theory”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 831-880.

Tesfatsion, L., (2007) “Agents Come to Bits: Towards a Constructive Comprehensive Taxonomy of Economic Entities”, Journal of Economic Behavior and Organization, Vol. 63, No. 2, June, pp. 333-346.

Tesfatsion, L., (2006) “Agent-Based Computational Modeling and Macroeconomics”, In Post Walrasian Macroeconomics: Beyond the Dynamic Stochastic General Equilibrium Model ed. Colander, D.; Cambridge University Press, Cambridge, pp. 175-202.

Zeidenberg, M., (2005) “Agent-Based Models of Urban Industrial Specialization“, In Proceedings of the Agent 2005 Conference on Generative Social Processes, Models, and Mechanisms ed. Macal, C.M., North, M.J. and Sallach, D.; ANL/DIS-06-5, Co-sponsored by Argonne National Laboratory and The University of Chicago, October 13-15, pp. 409-417.

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Emergency Responses

Christensen, K. and Sasaki, Y., (2008) “Agent-Based Emergency Evacuation Simulation with Individuals with Disabilities in the Population“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 3, June, 13 pp.

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Energy Markets

Ma, T. and Nakamori, Y., (2009) “Modeling Technological Change in Energy Systems – From Optimization to Agent-Based Modeling“, Energy, Vol. 34, No. 7, July, pp. 873-879.

Scholz, R. and Pyka, A., (2009) “A Neo-Schumpeterian Model of Energy Markets“, Cybernetics and Systems, Vol. 40, No. 5, pp. 418-440.

Sun, J. and Tesfatsion, L., (2007) “Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework”, Computational Economics, Vol. 30, No. 3, October, pp. 291-327. For more on this project and an extended version of this paper see here.

Weidlich, A. and Veit, D., (2008) “A Critical Survey of Agent-Based Wholesale Electricity Market Models”, Energy Economics, Vol. 30, No. 4, July, pp. 1728-1759.

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Epidemiology

Bian, L. and Liebner, D., (2007) “A Network Model for Dispersion of Communicable Diseases”, Transactions in GIS, Vol. 11, No. 2, April, pp. 155-173.

Devillers, H., Lobry, J.R. and Menu, F., (2008) “An Agent-Based Model for Predicting the Prevalence of Trypanosoma cruzi I and II in their Host and Vector Populations”, Journal of Theoretical Biology, Vol. 255, No. 3, 7 December, pp. 307-315.

Dunham, J.B., (2006) “An Agent-Based Spatially Explicit Epidemiological Model in MASON“, Journal of Artificial Societies and Social Simulation, Vol. 9, No. 1, January.

Epstein, J.M., (2009) “Modelling to Contain Pandemics“, Nature, Vol. 460, No. 7256, 6 August, pp. 687.

Eubank, S., Guclu, H., Anil Kumar, V.S., Marathe, M.V., Srinivasan, A., Toroczkai, Z. and Wang, N., (2004) “Modelling Disease Outbreaks in Realistic Urban Social Networks”, Nature, Vol. 429, No. 6988, 13 May, pp. 180-184.

Huang, C.-Y., Sun, C.-T., Hsieh, J.-L. and Lin, H., (2004) “Simulating SARS: Small-World Epidemiological Modeling and Public Health Policy Assessments“, Journal of Artificial Societies and Social Simulation, Vol. 7, No. 4, October.

Laperrière, V., Badariotti, D., Banos, A. and Müller, J.-P., (2009) “Structural Validation of an Individual-Based Model for Plague Epidemics Simulation”, Ecological Complexity, Vol. 6, No. 2, June, pp. 102-112.

Linard, C., Ponçon, N., Fontenille, D. and Lambin, E.F., (2009) “A Multi-Agent Simulation to Assess the Risk of Malaria Re-emergence in Southern France”, Ecological Modelling, Vol. 220, No. 2, January, pp. 160-174.

Perez, P. and Dray, A., (2005) “SIMDRUG: Exploring the Complexity of Heroin Use in Melbourne“, Drug Policy Modelling Project, Monograph 11, Fitzroy, Melbourne, Turning Point Alcohol & Drug Centre, December, 48 pp.

Stroud, P., Del Valle, S., Sydoriak, S., Riese, J. and Mniszewski, S., (2007) “Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society“, Journal of Artificial Societies and Social Simulation, Vol. 10, No. 4, 31 October, pp. 1-18.

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Finance

Arthur, W.B., Holland, J.H., LeBaron, B., Palmer, R. and Tayler, P., (1997) “Asset Pricing Under Endogenous Expectations in an Artificial Stock Market”, In The Economy as an Evolving Complex System II ed. Arthur, W.B., Durlauf, S.N. and Lane, D.A.; Westview Press, Boulder, pp. 15-44.

Hoffmann, A.O.I. and Von Eije, J.H., (2007) “Social Simulation of Stock Markets: Taking It to the Next Level“, Journal of Artificial Societies and Social Simulation, Vol. 10, No. 2, March, pp. 15.

LeBaron, B., (2000) “Agent-Based Computational Finance: Suggested Readings and Early Research”, Journal of Economic Dynamics & Control, Vol. 24, No. 5-7, June, pp. 679-702.

LeBaron, B., (2002) “Building the Santa Fe Artificial Stock Market“, Working Paper, Graduate School of International Economics and Finance, Brandeis University, June, 19 pp.

LeBaron, B., (2006) “Agent-Based Computational Finance”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1187-1233.

Palmer, R.G., Arthur, W.B., Holland, J.H., LeBaron, B. and Taylor, P., (1994) “Artificial Economic Life: A Simple Model of a Stock Market”, Physica D, Vol. 75, No. 1-3, 1 August, pp. 264-265.

Polhill, J.G. and Izquierdo, L.R., (2005) “Lessons Learned from Converting the Artificial Stock Market to Interval Arithmetic“, Journal of Artificial Societies and Social Simulation, Vol. 8, No. 2, March, pp. 13.

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Geography

Al-Ahmadi, K., See, L., Heppenstall, A. and Hogg, J., (2009) “Calibration of a Fuzzy Cellular Automata Model of Urban Dynamics in Saudi Arabia”, Ecological Complexity, Vol. 6, No. 2, June, pp. 80-101.

An, L., Linderman, M., Qi, J., Shortridge, A. and Liu, J., (2005) “Exploring Complexity in a Human-Environment System: An Agent-Based Spatial Model for Multidisciplinary and Multiscale Integration”, Annals of the Association of American Geographers, Vol. 95, No. 1, March, pp. 54-79.

Batty, M., (2005) Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals, MIT Press, Cambridge, MA & London, xxiii + 565 pp.

Brenner, T., (2001) “Simulating the Evolution of Localised Industrial Clusters – An Identification of the Basic Mechanism“, Journal of Artificial Societies and Social Simulation, Vol. 4, No. 3, June, pp. 1-28.

Brown, D.G. and Robinson, D.T., (2006) “Effects of Heterogeneity in Residential Preferences on an Agent-Based Model of Urban Sprawl“, Ecology and Society, Vol. 11, No. 1, 22 pp.

Castle, C.J.E. and Crooks, A.T., (2006) “Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations“, UCL Working Papers Series, Paper 110, Centre for Advanced Spatial Analysis, University College London, September, 60 pp.

Crooks, A.T., (2006) “Exploring Cities Using Agent Based Models and GIS“, UCL Working Papers Series, Paper 109, Centre for Advanced Spatial Analysis, University College London, September, 9 pp.

Crooks, A.T., (2012) “The Use of Agent-Based Modelling for Studying the Social and Physical Environment of Cities“, In Complexity and Planning: Systems, Assemblages and Simulations ed. De Roo, G., Hiller, J. and van Wezemael, J.; Ashgate, Burlington, VT, pp. 385-408.

Crooks, A.T., Castle, C.J.E. and Batty, M., (2007) “Key Challenges in Agent-Based Modelling for Geo-Spatial Simulation“, UCL Working Papers Series, Paper 121, Centre for Advanced Spatial Analysis, University College London, September, 37 pp.

Dibble, C., (2006) “Computational Laboratories for Spatial Agent-Based Models”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1511-1548.

Dibble, C. and Feldman, P.G., (2004) “The GeoGraph 3D Computational Laboratory: Network and Terrain Landscapes for RePast“, Journal of Artificial Societies and Social Simulation, Vol. 7, No. 1.

Groeneveld, J., Müller, B., Buchmann, C.M., Dressler, G., Guo, C., Hase, N., Hoffmann, F., John, F., Klassert, C., Lauf, T., Liebelt, V., Nolzen, H., Pannicke, N., Schulze, J., Weise, H. and Schwarz, N., (2017) “Theoretical Foundations of Human Decision-Making in Agent-Based Land Use Models – A Review“, Environmental Modelling & Software, Vol. 87, January, pp. 39-48.

Irwin, E.E. and Bockstael, N.G., (2002) “Interacting Agents, Spatial Externalities and the Evolution of Residential Land Use Patterns”, Journal of Economic Geography, Vol. 2, No. 1, January, pp. 31-54.

Parker, D.C., Manson, S.M., Janssen, M.A., Hoffmann, M.J. and Deadman, P., (2003) “Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review”, Annals of the Association of American Geographers, Vol. 93, No. 2, pp. 314-337.

Polhill, J.G., Parker, D., Brown, D. and Grimm, V., (2008) “Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 2, March, pp. 30.

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Innovation and Organisation Theory

Ahrweiler, P., Pyka, A. and Gilbert, N., (2004) “Simulating Knowledge Dynamics in Innovation Networks (SKIN)“, Working Paper No. 267, University of Augsburg, December, 10 pp.

Albino, V., Carbonara, N. and Giannoccaro, I., (2006) “Innovation in Industrial Districts: An Agent-Based Simulation Model”, International Journal of Production Economics, Vol. 104, No. 1, November, pp. 30-45.

Cartier, M., (2004) “An Agent-Based Model of Innovation Emergence in Organizations: Renault and Ford Through the Lens of Evolutionism”, Computational & Mathematical Organization Theory, Vol. 10, No. 2, pp. 147-153.

Dawid, H., (2006) “Agent-Based Models of Innovation and Technological Change”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1235-1272.

Gilbert, N., Pyka, A. and Ahrweiler, P., (2001) “Innovation Networks – A Simulation Approach“, Journal of Artificial Societies and Social Simulation, Vol. 4, No. 3, June.

Ma, T. and Nakamori, Y., (2005) “Agent-Based Modeling on Technological Innovation as an Evolutionary Process”, European Journal of Operational Research, Vol. 166, No. 3, November, pp. 741-755.

Merlone, U., Sonnessa, M. and Terna, P., (2008) “Horizontal and Vertical Multiple Implementations in a Model of Industrial Districts“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 2, March, 25 pp.

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Learning

Izquierdo, S.S., Izquierdo, L.R. and Gotts, N.M., (2008) “Reinforcement Learning Dynamics in Social Dilemmas“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 2, March, pp. 22.

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Medicine

Bessonov, N., Demin, I., Pujo-Menjouet, L. and Volpert, V., (2009) “A Multi-Agent Model Describing Self-Renewal of Differentiation Effects on the Blood Cell Population”, Mathematical and Computer Modelling, Vol. 49, No. 11-12, June, pp. 2116-2127.

Bauer, A.L., Beauchemin, C.A.A. and Perelson, A.S., (2009) “Agent-Based Modeling of Host-Pathogen Systems: The Successes and Challenges”, Information Sciences, Vol. 179, No. 10, 29 April, pp. 1379-1389.

Textor, J. and Hansen, B., (2009) “Hybrid Simulation Algorithms for an Agent-Based Model of the Immune Response“, Cybernetics and Systems, Vol. 40, No. 5, pp. 390-417.

Zeng, Y. and Poh, K.-L., (2009) “Multi-Agent Graphical Decision Models in Medicine”, Applied Artificial Intelligence, Vol. 23, No. 1, January, pp. 103-122.

Zhang, L., Strouthos, C.G., Wang, Z. and Deisboeck, T.S., (2009) “Simulating Brain Tumor Heterogeneity with a Multiscale Agent-Based Model: Linking Molecular Signatures, Phenotypes and Expansion Rate”, Mathematical and Computer Modelling, Vol. 49, No. 1-2, January, pp. 307-319.

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Migration

Silveira, J.J., Espindola, A.L. and Penna, T.J.P., (2006) “Agent-Based Model to Rural-Urban Migration Analysis”, Physica A, Vol. 364, 15 May, pp. 445-456.

Hassani-Mahmooei, B. and Parris, B.W., (2012) “Climate Change and Internal Migration Patterns in Bangladesh: An Agent-Based Model“, Environment and Development Economics, Vol. 17, No. 6, December, pp. 763-780.

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Operations Research

Albino, V., Carbonara, N. and Giannoccaro, I., (2007) “Supply Chain Cooperation in Industrial Districts: A Simulation Analysis”, European Journal of Operational Research, Vol. 177, No. 1, February, pp. 261-280.

Chiaramonte, M.V. and Chiaramonte, L.M., (2008) “An Agent-Based Nurse Rostering System Under Minimal Staffing Conditions”, International Journal of Production Economics, Vol. 114, No. 2, August, pp. 697-713.

Gao, Y., Shang, Z. and Kokossis, A., (2009) “Agent-Based Intelligent System Development for Decision Support in Chemical Process Industry”, Expert Systems with Applications, Vol. 36, No. 8, October, pp. 11099-11107.

Paolucci, M. and Sacile, R., (2004) Agent-Based Manufacturing and Control Systems: New Agile Manufacturing Solutions for Achieving Peak Performance, APICS Series on Resource Management; CRC Press, Boca Raton, FL & London, xviii + 269 pp.

Tetiker, M.D., Artel, A., Teymour, F. and Cinar, A., (2008) “Control of Grade Transitions in Distributed Chemical Reactor Networks – An Agent-Based Approach”, Computers & Chemical Engineering, Vol. 32, No. 9, 26 September, pp. 1984-1994.

Tykhonov, D., Jonker, C., Meijer, S. and Verwaart, T., (2008) “Agent-Based Simulation of the Trust and Tracing Game for Supply Chains and Networks“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 3, June, 30 pp.

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Peacekeeping

Schwarz, G. and Lampe, T., (2005) “Experiments with PAX: A Quick Guide“, Friedrichshafen, Germany, EADS Deutschland GmbH, System Design Center, July, 16 pp.

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Political Science

Cederman, L.-E., (2001) “Agent-Based Modeling in Political Science”, The Political Methodologist, Vol. 10, No. 1, Fall, pp. 16-22.

Cederman, L.-E., (2002) “Endogenizing Geopolitical Boundaries with Agent-Based Modeling”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, Supplement 3, 14 May, pp. 7296-7303.

Cederman, L.-E., (2003) “Modelling the Size of Wars: From Billiard Balls to Sand Piles”, American Political Science Review, Vol. 97, No. 1, February, pp. 135-150.

Epstein, J.M., (2002) “Modeling Civil Violence: An Agent-Based Computational Approach”, Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, Supplement 3, 14 May, pp. 7243-7250.

Kollman, K. and Page, S.E., (2006) “Computational Methods and Models of Politics”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1433-1463.

Lim, M., Metzler, R. and Bar-Yam, Y., (2007) “Global Pattern Formation and Ethnic/Cultural Violence”, Science, Vol. 317, No. 5844, 14 September, pp. 1540-1544.

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Sociology

Hills, T. and Todd, P., (2008) “Population Heterogeneity and Individual Differences in an Assortative Agent-Based Marriage and Divorce Model (MADAM) Using Search with Relaxing Expectations“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 4, October, 16 pp.

Neumann, M., (2008) “Homo Socionicus: a Case Study of Simulation Models of Norms“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 4, October, 25 pp.

Schwenk, G. and Reimer, T., (2008) “Simple Heuristics in Complex Networks: Models of Social Influence“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 3, June, 18 pp.

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Terrorism

Carley, K.M., Fridsma, D.B., Casman, E., Yahja, A., Altman, N., Chen, L.-C., Kaminsky, B. and Nave, D., (2006) “BioWar: Scalable Agent-Based Model of Bioattacks”, IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 36, No. 2, March, pp. 252-265.

Elliott, E. and Kiel, L.D., (2004) “A Complex Systems Approach for Developing Public Policy Toward Terrorism: An Agent-Based Approach”, Chaos, Solitons & Fractals, Vol. 20, No. 1, April, pp. 63-68.

Keller, J.P., Desouza, K.C. and Lin, Y., (2010) “Dismantling Terrorist Networks: Evaluating Strategic Options Using Agent-Based Modeling”, Technological Forecasting and Social Change, Vol. 77, No. 7, September, pp. 1014-1036.

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Transport

Doniec, A., Mandiau, R., Piechowiak, S. and Espié, S., (2008) “A Behavioral Multi-Agent Model for Road Traffic Simulation”, Engineering Applications of Artificial Intelligence, Vol. 21, No. 8, December, pp. 1443-1454.

Gambardella, L.M., Rizzoli, A.E. and Funk, P., (2002) “Agent-based Planning and Simulation of Combined Rail/Road Transport”, SIMULATION, Vol. 78, No. 5, 1 May, pp. 293-303.

Schadschneider, A. and Seyfried, A., (2009) “Validation of CA Models of Pedestrian Dynamics with Fundamental Diagrams“, Cybernetics and Systems, Vol. 40, No. 5, pp. 367-389.

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ABM Design

Angus, S.D. and Hassani-Mahmooei, B., (2015) ““Anarchy” reigns: A quantitative analysis of agent-based modelling publication practices in JASSS, 2001-2012“, Journal of Artificial Societies and Social Simulation, Vol. 18, No. 4, 31 October.

Chen, S.-H., (2001) “On the Relevance of Genetic Programming to Evolutionary Economics”, In Evolutionary Controversies in Economics: A New Transdisciplinary Approach ed. Aruka, Y.; Japan Association for Evolutionary Economics, Springer-Verlag, Tokyo, pp. 135-150.

Chen, S.-H., (2002) “Fundamental Issues in the Use of Genetic Programming in Agent-Based Computational Economics”, In Agent-Based Approaches in Economic and Social Complex Systems ed. Namatame, A., Terano, T. and Kurumatani, K.; IOS Press, Amsterdam, pp. 208-220.

Davis, P.K., Bankes, S.C. and Egner, M., (2007) “Enhancing Strategic Planning with Massive Scenario Generation“, Technical Report TR-392, Santa Monica, CA; Arlington, VA & Pittsburgh, PA, RAND National Security Research Division, xvii + 58 pp.

Janssen, M.A. and Ostrom, E., (2006) “Empirically Based, Agent-Based Models“, Ecology and Society, Vol. 11, No. 2, 13 pp.

Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G., Huth, A., Jepsen, J.U., Jørgensen, C., Mooij, W.M., Müller, B., Pe’er, G., Piou, C., Railsback, S.F., Robbins, A.M., Robbins, M.M., Rossmanith, E., Rüger, N., Strand, E., Souissi, S., Stillman, R.A., Vabø, R., Visser, U. and DeAngelis, D.L., (2006) “A Standard Protocol for Describing Individual-Based and Agent-Based Models”, Ecological Modelling, Vol. 198, No. 1-2, 15 September, pp. 115-126.

Grimm, V., Berger, U., DeAngelis, D.L., Polhill, J.G., Giske, J. and Railsback, S.F., (2010) “The ODD Protocol: A Review and First Update”, Ecological Modelling, Vol. 221, No. 23, November, pp. 2760-2768.

Kleijnen, J.P.C., Sanchez, S.M., Lucas, T.W. and Cioppa, T.M., (2005) “A User’s Guide to the Brave New World of Designing Simulation Experiments”, INFORMS Journal on Computing, Vol. 17, No. 3, Summer, pp. 263-289.

Kornhauser, D., Wilensky, U. and Rand, W., (2009) “Design Guidelines for Agent Based Model Visualization“, Journal of Artificial Societies and Social Simulation, Vol. 12, No. 2, March, 27 pp.

Law, A.M., (2005) “How to Build Valid and Credible Simulation Models“, In Proceedings of the 2005 Winter Simulation Conference ed. Kuhl, M.E., Steiger, N.M., Armstrong, F.B. and Joines, J.A.; Orlando FL, December, pp. 24-32.

Lucas, T., Sanchez, S.M., Brown, L. and Vinyard, W., (2002) “Better Designs for High-Dimensional Explorations of Distillations“, Maneuver Warfare Science 2002, U.S. Marine Corps Combat Development Command, Quantico, VA, pp. 17-45.

Müller, B., Balbi, S., Buchmann, C.M., de Sousa, L., Dressler, G., Groeneveld, J., Klassert, C.J., Le, Q.B., Millington, J.D.A., Nolzen, H., Parker, D.C., Polhill, J.G., Schlüter, M., Schulze, J., Schwarz, N., Sun, Z., Taillandier, P. and Weise, H., (2014) “Standardised and Transparent Model Descriptions for Agent-Based Models: Current Status and Prospects“, Environmental Modelling & Software, Vol. 55, May, pp. 156-163.

Osgood, N., (2009) “Lightening the Performance Burden of Individual-Based Models through Dimensional Analysis and Scale Modeling”, System Dynamics Review, Vol. 25, No. 2, April – June, pp. 101-134.

Polhill, J.G., Izquierdo, L.R. and Gotts, N.M., (2005) “The Ghost in the Model (and Other Effects of Floating Point Arithmetic)“, Journal of Artificial Societies and Social Simulation, Vol. 8, No. 1, January, pp. 21.

Polhill, J.G., Izquierdo, L.R. and Gotts, N.M., (2006) “What Every Agent-Based Modeller Should Know About Floating Point Arithmetic”, Environmental Modelling & Software, Vol. 21, No. 3, March, pp. 283-309.

Ramanath, A.M. and Gilbert, N., (2004) “The Design of Participatory Agent-Based Social Simulations“, Journal of Artificial Societies and Social Simulation, Vol. 7, No. 4, October, pp. 13.

Sun, Z., Lorscheid, I., Millington, J.D., Lauf, S., Magliocca, N.R., Groeneveld, J., Balbi, S., Nolzen, H., Müller, B., Schulze, J. and Buchmann, C.M., (2016) “Simple or Complicated Agent-Based Models? A Complicated Issue“, Environmental Modelling & Software, Vol. 86, December, pp. 56-67.

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Verification and Validation

Balci, O., (2004) “Quality Assessment, Verification, and Validation of Modeling and Simulation Applications“, In Proceedings of the 2004 Winter Simulation Conference ed. Ingalls, R.G., Rossetti, M.D., Smith, J.S. and Peters, B.A.; Washington DC, 5-8 December, pp. 122-129.

Bianchi, C., Cirillo, P., Gallegati, M. and Vagliasindi, P., (2007) “Validating and Calibrating Agent-Based Models: A Case Study”, Computational Economics, Vol. 30, No. 3, October, pp. 245-264.

Brady, T.F. and Yellig, E., (2005) “Simulation Data Mining: A New Form of Computer Simulation Output“, In Proceedings of the 2005 Winter Simulation Conference ed. Kuhl, M.E., Steiger, N.M., Armstrong, F.B. and Joines, J.A.; Orlando FL, December, pp. 285-289.

Brenner, T. and Werker, C., (2007) “A Taxonomy of Inference in Simulation Models”, Computational Economics, Vol. 30, No. 3, October, pp. 227-244.

Fagiolo, G., Moneta, A. and Windrum, P., (2007) “A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems”, Computational Economics, Vol. 30, No. 3, October, pp. 195-226.

Law, A.M., (2004) “Statistical Analysis of Simulation Output Data: The Practical State of the Art“, In Proceedings of the 2004 Winter Simulation Conference ed. Ingalls, R.G., Rossetti, M.D., Smith, J.S. and Peters, B.A.; Washington DC, 5-8 December, pp. 67-72.

Marks, R.E., (2007) “Validating Simulation Models: A General Framework and Four Applied Examples”, Computational Economics, Vol. 30, No. 3, October, pp. 265-290.

Moss, S., (2008) “Alternative Approaches to the Empirical Validation of Agent-Based Models“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 1, January, 16 pp.

Takadama, K., Kawai, T. and Koyama, Y., (2008) “Micro- and Macro-Level Validation in Agent-Based Simulation: Reproduction of Human-Like Behaviors and Thinking in a Sequential Bargaining Game“, Journal of Artificial Societies and Social Simulation, Vol. 11, No. 2, March, 17 pp.

Tinvan, B.F., (2004) “Data Farming Coevolutionary Dynamics in Repast“, In Proceedings of the 2004 Winter Simulation Conference ed. Ingalls, R.G., Rossetti, M.D., Smith, J.S. and Peters, B.A.; Washington DC, 5-8 December, pp. 820-826.

Veglio, A. and Marsili, M., (2007) “Stochastic Analysis of an Agent-Based Model”, Physica A, Vol. 385, No. 2, 15 November, pp. 631-636.

Wilcox, S.P., (2005) “Agent-Based Models as Quantitative Sociological Methodology: Calibrating Simulation Models to Data and Finding Confidence Intervals for Model Parameters“, In Proceedings of the Agent 2005 Conference on Generative Social Processes, Models, and Mechanisms ed. Macal, C.M., North, M.J. and Sallach, D.; ANL/DIS-06-5, Co-sponsored by Argonne National Laboratory and The University of Chicago, October 13-15, pp. 215-234.

Windrum, P., Fagiolo, G. and Moneta, A., (2007) “Empirical Validation of Agent-Based Models: Alternatives and Prospects“, Journal of Artificial Societies and Social Simulation, Vol. 10, No. 2, March, 19 pp.

Ye, K.Q., (1998) “Orthogonal Column Latin Hypercubes and Their Application in Computer Experiments”, Journal of the American Statistical Association – Theory and Methods, Vol. 93, No. 444, December, pp. 1430-1439.

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Quotes

On ABMs’ ability to naturally model out-of-equilibrium behaviour

“This out-of-equilibrium approach is not a minor adjunct to standard economic theory; it is economics done in a more general way. When examined out of equilibrium, economic patterns sometimes simplify into a simple, homogeneous equilibrium of standard economics; but just as often they show perpetually novel and complex behavior.”

Arthur, W.B., (2006) “Out-of-Equilibrium Economics and Agent-Based Modeling”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.; North-Holland, Amsterdam, pp. 1551-1564; p. 1552.

On the suitability of ABMs for modelling co-ordination decisions
“Economic growth depends not only on how people make decisions but also upon how their decisions are coordinated. Because of this, aggregate outcomes can diverge from individual intentions. … Agent-based computational methods are ideally suited for studying the aspects of growth most affected by coordination issues.”
Howitt, P., (2006) “Coordination Issues in Long-Run Growth”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.; North-Holland, Amsterdam, pp. 1605-1624.; p. 1606.

After comparing six different approaches to modelling sustainable development policy

“Unambiguously, the most promising modelling approach seems to be the multi-agent simulation model. … It is our opinion that public scientific and R and D policy-makers and advisers should foster their development and use in universities, schools and research institutions.”
Boulanger, P.-M. and Bréchet, T., (2005) “Models for Policy-Making in Sustainable Development: The State of the Art and Perspectives for Research”, Ecological Economics, Vol. 55, No. 3, 15 November, pp. 337-350; p. 349. The six approaches compared were macro-econometric, general equilibrium, optimisation, Bayesian networks, system dynamics and multi-agent (agent-based) models.

On recognising that models of interactions can have “combinatorial complexities that make it difficult (if not impossible) to obtain closed-form solutions”
“[E]conomists often examine simple models in the search for ‘the’ cause of some economic phenomenon, and argue for a parsimonious explanation of their observations. This approach often ignores the possibility that the truth could be multidimensional, and that the multiple dimensions of reality could interact to produce phenomena that no one factor could explain. While we all like parsimony, true parsimony chooses a model as simple as possible without being too simple, and would not force our thinking into a conceptual straightjacket.”
Judd, K.L., (2006) “Computationally Intensive Analyses in Economics”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.; North-Holland, Amsterdam, pp. 881-893; p. 885.

On the trade-off between numerical errors and specification errors
“[N]umerical errors can be reduced through computation but correcting the specification errors of analytically tractable models is much more difficult. The issue is not whether we have errors, but where we put those errors. The key fact is that economists face a trade-off between the numerical errors in computational work and the specification errors of analytically tractable models.”
Judd, K.L., (2006) “Computationally Intensive Analyses in Economics”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.; North-Holland, Amsterdam, pp. 881-893; p. 887.

On the appeal of ABMs in political science
“In our view, complex systems and computational techniques will have a large and growing impact on research on politics in the near future. This optimism follows from the observation that the concepts used in computational methodology in general and agent-based models in particular resonate deeply within political science because of the domains of study in the discipline and because early findings from agent-based models align with widely known empirical regularities in the political world.”
Kollman, K. and Page, S.E., (2006) “Computational Methods and Models of Politics”, In Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics ed. Tesfatsion, L. and Judd, K.L.; North-Holland, Amsterdam, pp. 1433-1463; p. 1434.

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Links

Leigh Tesfatsion’s Agent-Based Modelling portal – The best site on the net for agent-based computational economics.

Repast – One of the best free agent-based modelling tools. Repast is very powerful but to get the most out of it requires Java or C# programming skills. For an excellent Repast tutorial by John Murphy (for Repast 3 not Simphony), click here.

Netlogo – Another one of the best free agent-based modelling tools. Netlogo is very well documented with dozens of demo programs with full code. See also:

MASON is another platform that is apparently quite good, though I haven’t used it.

CORMAS quoted by Sawyer in his Social Emergence-Societies as Complex Systems (2005) as one of the best platforms to tackle social complexity.

For an excellent introduction to agent-based computational economics, take a look at the materials from the Seventh Trento Summer School held in 2006.

Geographic Information Systems (GIS) & Agent-Based Modelling A useful blog by Andrew Crooks & Christian Castle.

University College London’s Centre for Advanced Spatial Analysis

Monash University’s VLABLots of good demos of agent-based modelling applications.

Open Agent Based Modeling Consortium Introduced and decscribed here.

Journal of Artificial Societies and Social Simulation (JASSS) – An excellent online peer-reviewed journal.

Society for Economic Science with Heterogeneous Interacting Agents (ESHIA)

European Social Simulation Association

WinterSim – An annual conference held in the (Northern) Winter.

Java programming & other software:

Get the free Java SE Development Kit (JDK) and Java Runtime Environment (JRE) from Oracle here.

For Java tutorials from Oracle click here.

Big Faceless Java Graph Library – “A class library for creating industry leading Graphs and Charts in Java”.

Java Topology Suite – An open source class library for 2D spatial work.

JGAP – Java Genetic Algorithms Package: “JGAP is a Genetic Algorithms and Genetic Programming component provided as a Java framework. It provides basic genetic mechanisms that can be easily used to apply evolutionary principles to problem solutions.”

Weka – Data mining software in Java. “Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code.”

Eclipse is one of the best Integrated Development Environments for Java programming.

For UML try Visual Paradigm. The Community version is free.

For Geographic Information Systems (GIS), Manifold is fantastic – and far cheaper than ESRI’s ArcGIS suite.

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Last updated: 21 July 2017 Copyright © Brett Parris, 2011-2017.