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Does Reinforcement Learning Simulate Threshold Public Goods Games?: A Comparison with Subject Experiments
Sobei H. ODA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2003/08/01
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Software Agent and Its Applications)
reinforcement learning, agent-based computational economics, experimental economics, public goods,
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This paper examines the descriptive power and the limitations of a simple reinforcement learning model (REL), comparing the simulation results with the results of an economic experiment employing human subjects. Agent-based computational economics and experimental economics are becoming increasingly popular as tools for economists. A new variety of learning model using games with a unique equilibrium is proposed and examined in both of the fields mentioned above. However, little attention is given to games with multiple equilibria. We examine threshold public goods games with two types of equilibria, where each player in a five-person group simultaneously contributes the public goods from her private endowments. In the experiments, we observe two patterns of the subjects' behavior: the cooperative and non-cooperative patterns. Our simulation results show that the REL reproduces the cooperative pattern, but does not reproduce the non-cooperative pattern. However, the results suggest that the REL does reproduce the non-cooperative pattern in terms of the agents' internal states. That implies that deterministic strategies would be required to reproduce the non-cooperative pattern in the games. We show an example of the REL with deterministic strategies.