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Voting cycles when a dominant point exists

Author

Listed:
  • Vjollca Sadiraj
  • Jan Tuinstra
  • Frans van Winden

Abstract

We conduct experiments in which humans repeatedly play one of two games against a computer decision maker that follows either a reinforcement learning or an Experience Weighted Attraction algorithm. Our experiments show these learning algorithms more sensitively detect exploitable opportunities than humans. Also, learning algorithms respond to detected payoff increasing opportunities systematically; however, the responses are too weak to improve the algorithms payoffs. Human play against various decision maker types doesn't significantly vary. These factors lead to a strong linear relationship between the humans and algorithms action choice proportions that is suggestive of the algorithm's best response correspondence.

Suggested Citation

  • Vjollca Sadiraj & Jan Tuinstra & Frans van Winden, 2005. "Voting cycles when a dominant point exists," Experimental Economics Center Working Paper Series 2006-16, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
  • Handle: RePEc:exc:wpaper:2006-16
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    File URL: http://excen.gsu.edu/workingpapers/GSU_EXCEN_WP_2006-16.pdf
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    More about this item

    JEL classification:

    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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