ABSTRACT
Agent-based models are a popular way to explore the dynamics of human interactions, but rarely are these models based on empirical observations of actual human behavior. Here we exploit data collected in an experimental setting where over 150 human players played in a series of almost a hundred public goods games. First, we fit a series of deterministic models to the data, finding that a reasonably parsimonious model with just three parameters performs extremely well on the standard test of predicting average contributions. This same model, however, performs extremely poorly when predicting the full distribution of contributions, which is strongly bimodal. In response, we introduce and test a corresponding series of stochastic models, thus identifying a model that both predicts average contribution and also the full distribution. Finally, we deploy this model to explore hypotheses about regions of the parameter space outside of what was experimentally accessible. In particular, we investigate (a) whether a previous conclusion that network topology does not impact contribution levels holds for much larger networks than could be studied in a lab; (b) to what extent observed contributions depend on average network degree and variance in the degree distribution, and (c) the dependency of contributions on degree assortativity as well as the correlation between the generosity of players and the degree of the nodes to which they are assigned.
- Axelrod, R. 1984. The Evolution of Cooperation. Basic Books.Google Scholar
- Axelrod, R. 1997. The complexity of cooperation: Agent-based models of competition and collaboration. Princeton University Press.Google Scholar
- 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 99, Suppl 3, 7280--7287.Google ScholarCross Ref
- Camerer, C. and Hua Ho, T. 1999. Experience-weighted attraction learning in normal form games. Econometrica 67, 827--874.Google ScholarCross Ref
- Castillo, D. and Saysel, A. 2005. Simulation of common pool resource field experiments: a behavioral model of collective action. Ecological economics 55, 3, 420--436.Google Scholar
- Cederman, L. 1997. Emergent actors in world politics: how states and nations develop and dissolve. Princeton University Press.Google Scholar
- Deadman, P. 1999. Modelling individual behaviour and group performance in an intelligent agent-based simulation of the tragedy of the commons. Journal of Environmental Management 56, 3, 159--172.Google ScholarCross Ref
- Deffuant, G., Neau, D., Amblard, F., and Weisbuch, G. 2000. Mixing beliefs among interacting agents. Advances in Complex Systems 3, 01n04, 87--98.Google Scholar
- Epstein, J. and Axtell, R. 1996. Growing artificial societies: social science from the bottom up. MIT press. Google ScholarDigital Library
- Fischbacher, U., Gachter, S., and Fehr, E. 2001. Are people conditionally cooperative? evidence from a public goods experiment. Economics Letters 71, 3, 397--404.Google ScholarCross Ref
- Glance, N. S. and Huberman, B. A. 1993. The outbreak of cooperation. Journal of Mathematical sociology 17, 4, 281--302.Google ScholarCross Ref
- Heckbert, S., Baynes, T., and Reeson, A. 2010. Agent-based modeling in ecological economics. Annals of the New York Academy of Sciences 1185, 1, 39--53.Google ScholarCross Ref
- Holland, J. and Miller, J. 1991. Artificial adaptive agents in economic theory. The American Economic Review, 365--370.Google Scholar
- Janssen, M. and Ahn, T. 2006. Learning, signaling, and social preferences in public-good games. Ecology and Society 11, 2, 21.Google ScholarCross Ref
- Janssen, M. and Ostrom, E. 2006. Empirically based, agent-based models. Ecology and Society 11, 2, 37.Google ScholarCross Ref
- Kreps, D. M., Milgrom, P., Roberts, J., and Wilson, R. 1982. Rational cooperation in the finitely repeated prisoners' dilemma. Journal of Economic theory 27, 2, 245--252.Google ScholarCross Ref
- Lazer, D. and Friedman, A. 2007. The network structure of exploration and exploitation. Administrative Science Quarterly 52, 4, 667--694.Google ScholarCross Ref
- Ledyard, J. 1995. Public goods: A survey of experimental research. In Handbook of Experimental Economics, J. H. Hagel and A. E. Roth, Eds. Princeton University Press, Princeton, NJ, 111--194.Google Scholar
- Lopez-Pintado, D. and Watts, D. J. 2008. Social influence, binary decisions and collective dynamics. Rationality and Society 20, 4, 399--443.Google ScholarCross Ref
- Macy, M. and Willer, R. 2002. From factors to actors: Computational sociology and agent-based modeling. Annual review of sociology, 143--166.Google Scholar
- Mason, W. and Watts, D. 2012. Collaborative learning in networks. Proceedings of the National Academy of Sciences 109, 3, 764--769.Google ScholarCross Ref
- Newman, M. E. 2003. The structure and function of complex networks. SIAM review 45, 2, 167--256.Google Scholar
- Schelling, T. 1978. Micromotives and Macrobehavior. WW Norton.Google Scholar
- Suri, S. and Watts, D. J. 2011. Cooperation and contagion in web-based, networked public goods experiments. PLoS One 6, 3.Google ScholarCross Ref
- Wang, J., Suri, S., and Watts, D. 2012. Cooperation and assortativity with dynamic partner updating. Proceedings of the National Academy of Sciences 109, 36, 14363--14368.Google ScholarCross Ref
- Williams, J. B. 1938. The Theory of Investment Value. Harvard University Press.Google Scholar
- Wright, J. R. and Leyton-Brown, K. 2012. Behavioral game-theoretic models: A bayesian framework for parameter analysis. Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems. Google ScholarDigital Library
Index Terms
- Empirical agent based models of cooperation in public goods games
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