Social preferences in the public goods game–An Agent-Based simulation with EconSim

Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent’s utility, contribution, and voting behavior during the learning procedure. C...

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Vydáno v:PloS one Ročník 18; číslo 3; s. e0282112
Hlavní autoři: Bühren, Christoph, Haarde, Jan, Hirschmann, Christian, Kesten-Kühne, Janis
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Public Library of Science 15.03.2023
Public Library of Science (PLoS)
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ISSN:1932-6203, 1932-6203
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Shrnutí:Using a reinforcement-learning algorithm, we model an agent-based simulation of a public goods game with endogenous punishment institutions. We propose an outcome-based model of social preferences that determines the agent’s utility, contribution, and voting behavior during the learning procedure. Comparing our simulation to experimental evidence, we find that the model can replicate human behavior and we can explain the underlying motives of this behavior. We argue that our approach can be generalized to more complex simulations of human behavior.
Bibliografie:ObjectType-Article-1
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0282112