Summary
Agent-based models (ABMs) are increasingly used in studying complex adaptive systems. Micro-level interactions between heterogeneous agents are at the heart of recent advances in modelling of problems in the social sciences, including economics, political science, sociology, geography and demography, and related disciplines such as ecology and environmental sciences. Scientific journals and societies related to ABMs have flourished. Some of the trends will be discussed, both in terms of the underlying principles and the fields of application, some of which are introduced in the contributions to this book.
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References
Axelrod, R. (1997) The Complexity of Cooperation. Agent-Based Models of Competition and Collaboration. Princeton University Press, Princeton.
Axtell, R. (2000) Why agents? On the varied motivations for agent computing in the social sciences. Washington, The Brookings Institution, Center on Social and Economic Dynamics, 22 p. (CSED Working Paper, n 17). Available online at: http://www.brook.edu/dybdocroot/es/dynamics/papers/agents/agents.htm.
Billari, F.C. (2000) Searching for mates using ‘fast and frugal’ heuristics: a demographic perspective. In:: Gerard Ballot and Gerard Weisbuch (ed.), Applications of simulation to social sciences, p. 53–65. Oxford, Hermes Science Publications, 461 p.
Billari, F.C., Prskawetz, A. (ed.) (2003) Agent-Based Computational Demography. Using Simulation to Improve our Understanding of Demographic Behaviour, Heidelberg, Physica/Springer.
Billari, F.C., Ongaro, F. and Prskawetz, A. (2003) Introduction: agent-based computational demography. In: Prskawetz, A. (ed.) Agent-Based Computational Demography. Using Simulation to Improve our Understanding of Demographic Behaviour, Heidelberg, Physica/Springer Billari and Prskawetz (2003), pp. 1–17.
Becker, G.S. (1981) A treatise on the family. Cambridge (Mass.), Harvard University Press (2nd edition 1991).
Behrman, J.R. (2001) Why micro matters. In: Nancy Birdsall, Allen C. Kelley and Steven W. Sinding (ed.), Population matters. Demographic change, economic growth and poverty in the developing world, p. 371–410. Oxford, Oxford University Press.
Coleman, J.S. (1990) Foundations of Social Theory. Cambridge (Massaschussetts), Belknap Press.
Conte, R., Castelfranchi, C. (1995) Cognitive and social action. London, UCL Press limited.
Courgeau, D. (1995) Migration theories and behavioral models. International Journal of Population Geography, vol. 1, no.1, p. 19–27.
Courgeau, D. (2003) General introduction. In: Daniel Courgeau, Methodology and epistemology of multilevel analysis. Approaches from different social sciences, p. 1–23. Boston, Dordrecht and London, Kluwer Academic Publishers.
Epstein, J.M., Axtell, R. (1997) Growing Artificial Societies. Cambridge MIT Press.
Gaylord, R.J., D’Andria, L.J. (1998) Simulating Society-A Mathematica Toolkit for Modeling Socioeconomic Behaviour. Heidelberg, Springer/Telos.
Gilbert, N., Troitzsch, K.G. (2000) Simulation for the Social Scientist. Buckingham, PA, Open University Press.
Grimm, V. (1999) Ten years of individual-based modeling in ecology. What have we learned, and what could we learn in the future? Ecological Modelling, vol. 115, no. 2–3, p. 129–148.
Grimm, V. and Railsback, S.F. (2005) Individual-based Modeling and Ecology. Princeton, Princeton University Press.
Haken, H. (1977) Synergetics. Heidelberg, Springer.
Halpin, B. (1999) Simulation in Society. American Behavioral Scientist 42(10), p. 1488–1508.
Hammel, E.A., McDaniel, C.K. and Wachter, K.W. (1979) Demographic consequences of incest tabus: a microsimulation analysis, Science, vol. 205, no. 4410, p. 972–977.
Hammel, E.A. and Wachter, K.W. (1996) Evaluating the Slavonian Census of 1698. Part II: A microsimulation test and extension of the evidence. European Journal of Population, vol. 12, no. 4, p. 295–326.
Hedström, P. and Swedberg, R. (1999) Social mechanisms. An analytical approach to social theory. New York and Cambridge (UK), Cambridge University Press.
Helbing, D. (1995) Quantitative Sociodynamics Stochastic Methods and Models of Social Interaction Processes. Boston/London/Dordrecht: Kluwer.
Johnson, P.E. (1999) Simulation Modeling in Political Science. American Behavioral Scientist 42(10), p. 1509–1530.
Kirman, A.P. (1992) Whom or what does the representative individual represent?, Journal of Economic Perspectives, vol. 6, no. 2, p. 117–136.
Land, K.C. (1986) Method for national population forecasts: a review. Journal of the American Statistical Association, vol. 81, no. 347, p. 888–901.
Macy, M.W., Willer, R. (2002) From Factors to Actors: Computational Sociology and Agent-Based Modeling. Annual Review of Sociology 28, p. 143–166.
Nakazawa, M. and Ohtsuka, R. (1997) Analysis of completed parity using microsimulation modeling. Mathematical Population Studies, vol. 6, n 3, p. 173–186.
Rahmandad, H. and Sterman, J. (2004) Heterogeneity and network structure in the dynamics of diffusion: comparing agent-based and differential equation models. Cambridge (Massachussets), Massachussetts Institute of Technology (MIT Sloan Working Paper 4512-04).
Ridley, J.C. and Sheps, M.C. (1996) An analytic simulation model of human reproduction with demographic and biological components, Population Studies, vol. 19, no. 3, p. 297–310.
Ruggles, S. (1993) Confessions of a microsimulator. Historical methods, vol. 26, no. 4, p. 161–169.
Scheffran, J. (2006) Tools in Stakeholder Assessment and Interaction. In: S. Stoll-Kleemann, M. Welp (Eds.), Stakeholder dialogues in natural resources management and integrated assessments: Theory and practice (forthcoming).
Schelling, T.C. (1978) Micromotives and Macrobehavior New York: Norton.
Schweitzer, F. (ed.) (1997) Self-Organization of Complex Structures: From Individual to Collective Dynamics, vol. II. London, Gordon and Breach.
Tesfatsion, L. (Eds.) (2001) Special Issue of Agent-Based Computational Economics. Journal of Economic Dynamics & Control 25, p. 281–654.
Tomassini, C. and Wolf, D. (2000) Shrinking kin networks in Italy due to sustained low fertility, European Journal of Population, vol. 16, no. 4, p. 353–372.
van den Bergh, J. C.J.M. and Gowdy, J.M. (2003) The microfoundations of macroeconomics: an evolutionary perspective. Cambridge Journal of Economics, vol. 27, no. 1, p. 65–84.
van Imhoff, E. and Post, W.J. (1998) Microsimulation methods for population projection. Population: An English Selection, vol. 10, no. 1, p. 971–938. (Special issue on “New Methodological Approaches in the Social Sciences”).
Wachter, K. W. (1987) Microsimulation of household cycles. In: Bongaarts, J., Burch, T. K., Wachter, K.W. (Eds.): Family demography. Methods and their application, Clarendon Press, Oxford.
Weidlich, W. (2000) Sociodynamics-A Systematic Approach to Mathematical Modelling in the Social Sciences. Harwood Academic Publishers.
Wolf, D. (2001) The role of microsimulation in longitudinal data analysis. Canadian Studies in Population, vol. 28, n 2, p. 313–339.
Wolfram, S. (2002) A New Kind of Science. Champaign, Wolfram Research.
Zimmermann, K.F. and Vogler, M. (ed.) (2003) Family, Household and Work. Heidelberg, Springer.
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Billari, F.C., Fent, T., Prskawetz, A., Scheffran, J. (2006). Agent-Based Computational Modelling: An Introduction. In: Billari, F.C., Fent, T., Prskawetz, A., Scheffran, J. (eds) Agent-Based Computational Modelling. Contributions to Economics. Physica-Verlag HD. https://doi.org/10.1007/3-7908-1721-X_1
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