Abstract
In order to analyze equilibrium selection and coordination failure in coordination games, we develop an agent-based simulation system in which artificial adaptive agents have a decision making and learning mechanism based on neural networks and genetic algorithms. Using this simulation system, we examine the strategy choices of agents and formation of equilibria in a steady state, and compare our simulation result with the experimental result given by Van Huyck et al. (1990).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Axelrod, R.: Advancing the art of simulation in the social sciences. In: Conte, R., Hegselmann, R., Terna, R. (eds.) Simulating Social Phenomena, pp. 21–40. Springer (1997)
Andreoni, J., Miller, J.H.: Auctions with artificial adaptive agents. Games and Economic Behavior 10, 39–64 (1995)
Banerje, B., Sen, S.: Selecting parters. In: Parsons, S., Gmytrasiewicz, P., Wooldridge, M. (eds.) Game Theory and Decision Theory in Agent-Based Systems, pp. 27–42. Kluwer Academic Publishers, Dordrecht (2002)
Battalio, R., Samuelson, L., Van Huyck, J.: Optimization incentives and coordination failure in laboratory stag hunt games. Econometrica 69, 749–764 (2001)
Clark, K., Kay, S., Sefton, M.: When are Nash equilibria self-enforcing? An experimental analysis. International Journal of Game Theory 29, 495–515 (2001)
Cooper, R.W., DeJoong, D.V., Forsythe, R., Ross, T.W.: Communication in the battle of the sexes game: some experimental results. RAND Journal of Economics 20, 568–587 (1989)
Cooper, R.W., DeJoong, D.V., Forsythe, R., Ross, T.W.: Selection criteria in coordination games: some experimental results. American Economic Review 80, 218–233 (1990)
Cooper, R.W., DeJoong, D.V., Forsythe, R., Ross, T.W.: Communication in coordination games. The Quarterly Journal of Economics 107, 739–771 (1992)
Dorsey, R.E., Johnson, J.D., Van Boening, M.V.: The use of artificial neural networks for estimation of decision surfaces in first price sealed bid auctions. In: Cooper, W.W., Whinston, A.B. (eds.) New Directions in Computational Economics, pp. 19–40. Kluwer (1994)
Duffy, J., Hopkins, E.: Learning, information, and sorting in market entry games: theory and evidence. Games and Economic Behavior 51, 31–62 (2005)
Erev, I., Rapoport, A.: “Coordination, “magic,” and reinforcement learning in a market entry game. Games and Economic Behavior 23, 146–175 (1998)
Erev, I., Roth, A.E.: Predicting how people play games: reinforcement learning in experimental games with unique, mixed strategy equilibria. The American Economic Review 88, 848–881 (1998)
Friedman, D.: Equilibrium in evolutionary games: some experimental results. The Economic Journal 106, 1–25 (1996)
Fundenberg, D., Levine, D.K.: The Theory of Learning in Games. The MIT Press, Cambridge (1998)
Goeree, J.K., Holt, C.A.: An experimental study of costly coordination. Games and Economic Behavior 51, 349–364 (2005)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison Wesley, Massachusetts (1989)
Hassoun, M.H.: Fundamentals of Artificial Neural Networks. The MIT Press, Cambridge (1995)
Holland, J.H., Miller, J.H.: Adaptive intelligent agents in economic theory. American Economic Review 81, 365–370 (1991)
Leshno, M., Moller, D., Ein-Dor, P.: Neural nets in a group decision process. International Journal of Game Theory 31, 447–467 (2002)
Morgan, J., Sefton, M.: An experimental investigation of unprofitable games. Games and Economic Behavior 40, 123–146 (2002)
Ochs, J.: The coordination problem in decentralized markets: an experiment. The Quarterly Journal of Economics 105, 545–559 (1990)
Ochs, J.: Coordination problems. In: Kagel, J.H., Roth, A.E. (eds.) Handbook of Experimental Economics, ch. 3, pp. 195–251. Priceton University Press, Priceton (1995)
Rapoport, A., Seale, D.A., Winter, E.: Coordination and learning behavior in large groups with asymmetric players. Games and Economic Behavior 39, 111–136 (2002)
Roth, A.E., Erev, I.: Learning in extensive form games: experimental data and simple dynamic models in the intermediate term. Games and Economic Behavior 8, 163–212 (1995)
Schmidt, D., Shupp, R., Walker, J.M., Ostrom, E.: Playing safe in coordination games: the role of risk dominance, payoff dominance, and history of play. Games and Economic Behavior 42, 281–299 (2003)
Straub, P.G.: Risk dominance and coordination failures in static games. The Quarterly Review of Economics and Finance 35, 339–363 (1995)
Sundali, J.A., Rapoport, A., Seale, D.A.: Coordination in market entry games with symmetric players. Organizational Behavior and Human Decision Processes 64, 203–218 (1995)
Van Huyck, J.B., Battalio, R.C., Rankin, F.W.: On the origin of convention: evidence from coordination games. The Economic Journal 107, 576–596 (1997)
Van Huyck, J.B., Battalio, R.C., Beil, R.O.: Tacit coordination games, strategic uncertainty, and coordination failure. American Economic Review 80, 234–248 (1990)
Van Huyck, J.B., Battalio, R.C., Beil, R.O.: Strategic uncertainty, equilibrium selection, and coordination failure in average opinion games. The Quarterly Journal of Economics 106, 885–910 (1991)
Young, H.P.: Individual Strategy and Social Structure. Princeton University Press, Princeton (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Nishizaki, I., Hayashida, T., Hara, N. (2013). Agent-Based Simulation Analysis for Equilibrium Selection and Coordination Failure in Coordination Games Characterized by the Minimum Strategy. In: Nguyen, N.T. (eds) Transactions on Computational Collective Intelligence IX. Lecture Notes in Computer Science, vol 7770. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36815-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-36815-8_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36814-1
Online ISBN: 978-3-642-36815-8
eBook Packages: Computer ScienceComputer Science (R0)