What is it about?
We simulate human behavior in dilemmas and propose a model for social preferences that may explain behavior. Our simulation can replicate the behavior in previous experiments, and we can analyze the underlying motives with our model. We use a reinforcement algorithm and novel software to program the agent-based simulation - EconSim. The dilemma is a public goods game with the possibility to vote for punishment institutions.
Photo by David Pupaza on Unsplash
Why is it important?
The combination of experimental evidence and simulations is a fruitful avenue to better understand human behavior. Our social preference model combines different motives that previous research found to be relevant for explaining behavior in social interactions. We argue that our approach can be generalized to complex simulations of human behavior.
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This page is a summary of: Social preferences in the public goods game–An Agent-Based simulation with EconSim, PLoS ONE, March 2023, PLOS, DOI: 10.1371/journal.pone.0282112.
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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.
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