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. 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.

• Publication year

  2023

• Venue

  PLoS ONE

• Publication date

  2023-03-15

• Fields of study

  Medicine, Economics

• Identifiers
  DOI 10.1371/journal.pone.0282112PMID 36920889PMCID 10016715
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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