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Coordination games, anti-coordination games, and imitative learning

Published online by Cambridge University Press:  26 February 2014

Roger A. McCain  and
Richard Hamilton
Roger A. McCain
Affiliation:
Department of Economics and International Business, Drexel University, Philadelphia, PA 19104; Department of Emergency Medicine, Drexel University College of Medicine, Philadelphia, PA 19102. mccainra@drexel.eduhttp://faculty.lebow.drexel.edu/mccainr/Richard.Hamilton@drexelmed.eduhttps://www.drexelmed.edu/Home/AboutOurFaculty/RichardHamilton.aspx
Richard Hamilton
Affiliation:
Department of Economics and International Business, Drexel University, Philadelphia, PA 19104; Department of Emergency Medicine, Drexel University College of Medicine, Philadelphia, PA 19102. mccainra@drexel.eduhttp://faculty.lebow.drexel.edu/mccainr/Richard.Hamilton@drexelmed.eduhttps://www.drexelmed.edu/Home/AboutOurFaculty/RichardHamilton.aspx
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Abstract

Bentley et al.'s scheme generates distributions characteristic of situations of high and low social influence on decisions and of high and low salience (“transparency”) of rewards. Another element of decisions that may influence the placement of a decision process in their map is the way in which individual decisions interact to determine the payoffs. This commentary discusses the role of Nash equilibria in game theory, focusing especially on coordination and anti-coordination games.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 37 , Issue 1 , February 2014 , pp. 90 - 91
Copyright
Copyright © Cambridge University Press 2014 

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References

Aumann, R. J. (2003) Presidential address. Games and Economic Behavior 45:2–14.CrossRefGoogle Scholar
Holland, J. & Miller, J. (1991) Artificial adaptive agents in economic theory. American Economic Review 81(2):365–70.Google Scholar
McCain, R. A., Hamilton, R. & Linnehan, F. (2011) The problem of emergency department overcrowding: Agent-based simulation and test by questionnaire. In: Lecture Notes in Economics and Mathematical Systems 652: Emergent results of artificial economics, ed. Osinga, S., Hofstede, G. J., & Verwaart, T., pp. 91–102. Springer Verlag.Google Scholar
Schelling, T. (1960) The strategy of conflict. Harvard University Press.Google Scholar