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An Extended Reinforcement Algorithm for Estimation of Human Behaviour in Experimental Congestion Games

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  • Thorsten Chmura
  • Thomas Pitz

Abstract

The paper reports simulations applied on two similar congestion games: the first is the classical minority game. The second one is an asymmetric variation of the minority game with linear payoff functions. For each game, simulation results based on an extended reinforcement algorithm are compared with real experimental statistics. It is shown that the extension of the reinforcement model is essential for fitting the experimental data and estimating the player's behaviour.

Suggested Citation

  • Thorsten Chmura & Thomas Pitz, 2007. "An Extended Reinforcement Algorithm for Estimation of Human Behaviour in Experimental Congestion Games," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-1.
  • Handle: RePEc:jas:jasssj:2006-47-3
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    References listed on IDEAS

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    Cited by:

    1. Scott Moss, 2007. "Alternative Approaches to the Empirical Validation of Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(1), pages 1-5.
    2. Epstein, Daniel & Bazzan, Ana L.C., 2013. "The value of less connected agents in Boolean networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5387-5398.
    3. Enrica Carbone & Vinayak V. Dixit & E. Elisabet Rutstrom, 2022. "Should I stay or should I go? Congestion pricing and equilibrium selection in a transportation network," Theory and Decision, Springer, vol. 93(3), pages 535-562, October.

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