dorsal/arxiv
View SchemaHow individuals learn to take turns: Emergence of alternating cooperation in a congestion game and the prisoner's dilemma
| Authors | Dirk Helbing, Martin Schonhof, Hans-Ulrich Stark, Janusz A. Holyst |
|---|---|
| Categories | |
| ArXiv ID | physics/0504189 |
| URL | https://arxiv.org/abs/physics/0504189 |
| Journal | Advances in Complex Systems 8(1), 87-116 (2005) |
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.
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"abstract": "In many social dilemmas, individuals tend to generate a situation with low\npayoffs instead of a system optimum (\"tragedy of the commons\"). Is the routing\nof traffic a similar problem? In order to address this question, we present\nexperimental results on humans playing a route choice game in a computer\nlaboratory, which allow one to study decision behavior in repeated games beyond\nthe Prisoner\u0027s Dilemma. We will focus on whether individuals manage to find a\ncooperative and fair solution compatible with the system-optimal road usage. We\nfind that individuals tend towards a user equilibrium with equal travel times\nin the beginning. However, after many iterations, they often establish a\ncoherent oscillatory behavior, as taking turns performs better than applying\npure or mixed strategies. The resulting behavior is fair and compatible with\nsystem-optimal road usage. In spite of the complex dynamics leading to\ncoordinated oscillations, we have identified mathematical relationships\nquantifying the observed transition process. Our main experimental discoveries\nfor 2- and 4-person games can be explained with a novel reinforcement learning\nmodel for an arbitrary number of persons, which is based on past experience and\ntrial-and-error behavior. Gains in the average payoff seem to be an important\ndriving force for the innovation of time-dependent response patterns, i.e. the\nevolution of more complex strategies. Our findings are relevant for decision\nsupport systems and routing in traffic or data networks.",
"arxiv_id": "physics/0504189",
"authors": [
"Dirk Helbing",
"Martin Schonhof",
"Hans-Ulrich Stark",
"Janusz A. Holyst"
],
"categories": [
"physics.soc-ph"
],
"journal_ref": "Advances in Complex Systems 8(1), 87-116 (2005)",
"title": "How individuals learn to take turns: Emergence of alternating cooperation in a congestion game and the prisoner\u0027s dilemma",
"url": "https://arxiv.org/abs/physics/0504189"
},
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