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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Veröffentlicht in:	PloS one Jg. 18; H. 3; S. e0282112
Hauptverfasser:	Bühren, Christoph, Haarde, Jan, Hirschmann, Christian, Kesten-Kühne, Janis
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 15.03.2023 Public Library of Science (PLoS)
Schlagworte:	Agent-based models Algorithms Analysis Biology and Life Sciences Computer and Information Sciences Computer Simulation Cooperation Cooperative Behavior Data mining Economic models Economic theory Endowment Experiments Game Theory Games Human acts Human behavior Human subjects Humans Laboratories Machine learning Methods Physical Sciences Preferences Public good Punishment Research and Analysis Methods Self interest Simulation Simulation methods Social Behavior Social Behavior Disorders Social Sciences Germany
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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Zusammenfassung:	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.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0282112