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http://ssrn.com/abstract=691801
 
 

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How Individuals Learn to Take Turns: Emergence of Alternating Cooperation in a Congestion Game and the Prisoner's Dilemma


Dirk Helbing


ETH Zürich - Department of Humanities, Social and Political Sciences (GESS); ETH Zürich

Martin Schoenhof


Dresden University of Technology - Institute for Transport and Economics

Hans-Ulrich Stark


Dresden University of Technology - Institute for Transport and Economics

Janusz Holyst


Warsaw University of Technology - Faculty of Physics; Warsaw University of Technology - Centre of Excellence for Complex Systems Research


Advances in Complex Systems, Vol. 8, pp. 87-116

Abstract:     
In many social dilemmas, individuals tend to generate a situation with low payoffs instead of a system optimum (tragedy of the commons). Is the routing of traffic a similar problem? In order to address this question, we present experimental results on humans playing a route choice game in a computer laboratory, which allow one to study decision behavior in repeated games beyond the Prisoner's Dilemma. We will focus on whether individuals manage to find a cooperative and fair solution compatible with the system-optimal road usage. We find that individuals tend towards a user equilibrium with equal travel times in the beginning. However, after many iterations, they often establish a coherent oscillatory behavior, as taking turns performs better than applying pure or mixed strategies. The resulting behavior is fair and compatible with system-optimal road usage. In spite of the complex dynamics leading to coordinated oscillations, we have identified mathematical relationships quantifying the observed transition process. Our main experimental discoveries for 2- and 4-person games can be explained with a novel reinforcement learning model for an arbitrary number of persons, which is based on past experience and trial-and-error behavior. Gains in the average payoff seem to be an important driving force for the innovation of time-dependent response patterns, i.e. the evolution of more complex strategies. Our findings are relevant for decision support systems and routing in traffic or data networks.

Number of Pages in PDF File: 28

Keywords: Game theory, reinforcement learning, multi-agent simulation

JEL Classification: C72, C73, C92, C91

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Date posted: April 15, 2005  

Suggested Citation

Helbing, Dirk and Schoenhof, Martin and Stark, Hans-Ulrich and Holyst, Janusz, How Individuals Learn to Take Turns: Emergence of Alternating Cooperation in a Congestion Game and the Prisoner's Dilemma. Advances in Complex Systems, Vol. 8, pp. 87-116. Available at SSRN: http://ssrn.com/abstract=691801

Contact Information

Dirk Helbing
Swiss Federal Institute of Technology Zurich - Department of Humanities, Social and Political Sciences (GESS) ( email )
ETH-Zentrum SEW E 26
CH-8092 Zurich
Switzerland
Swiss Federal Institute of Technology Zurich ( email )
Zürichbergstrasse 18
8092 Zurich, CH-1015
Switzerland
Martin Schoenhof (Contact Author)
Dresden University of Technology - Institute for Transport and Economics ( email )
Mommsenstrasse 13
D-01062 Dresden
Germany
+49/0 351 463-36721 (Phone)
+49/0 351 463-36809 (Fax)
Hans-Ulrich Stark
Dresden University of Technology - Institute for Transport and Economics ( email )
Mommsenstrasse 13
D-01062 Dresden
Germany
Janusz Holyst
Warsaw University of Technology - Faculty of Physics ( email )
Koszykowa 75
Warsaw, PL-00-662
Poland
Warsaw University of Technology - Centre of Excellence for Complex Systems Research ( email )
75 Koszykowa
Warsaw, PL-00-662
Poland
Feedback to SSRN


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