文章基本信息

标题：The Role of Reinforcement Learning in the Emergence of Conventions: Simulation Experiments with the Repeated Volunteer’s Dilemma
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作者：Hendrik Nunner ; Wojtek Przepiorka ; Chris Janssen 等
期刊名称：Journal of Artificial Societies and Social Simulation
印刷版ISSN：1460-7425
出版年度：2022
卷号：25
期号：1
DOI：10.18564/jasss.4771
语种：English
出版社：University of Surrey, Department of Sociology
摘要：We use reinforcement learning models to investigate the role of cognitive mechanisms in the emergence of conventions in the repeated volunteer’s dilemma (VOD). The VOD is a multi-person, binary choice collective goods game in which the contribution of only one individual is necessary and sufficient to produce a benefit for the entire group. Behavioral experiments show that in the symmetric VOD, where all group members have the same costs of volunteering, a turn-taking convention emerges, whereas in the asymmetric VOD, where one “strong” group member has lower costs of volunteering, a solitary-volunteering convention emerges with the strong member volunteering most of the time. We compare three different classes of reinforcement learning models in their ability to replicate these empirical findings. Our results confirm that reinforcement learning models can provide a parsimonious account of how humans tacitly agree on one course of action when encountering each other repeatedly in the same interaction situation. We find that considering contextual clues (i.e., reward structures) for strategy design (i.e., sequences of actions) and strategy selection (i.e., favoring equal distribution of costs) facilitate coordination when optima are less salient. Furthermore, our models produce better fits with the empirical data when agents act myopically (favoring current over expected future rewards) and the rewards for adhering to conventions are not delayed.
关键词：Conventions; Repeated Games; Volunteer’s Dilemma;Agent-Based Simulation;Reinforcement Learning;Cognitive Modeling