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On Playing with Emotion: A Spatial Evolutionary Variation of the Ultimatum Game
D Y Charcon1, L H A Monteiro1,2
1Escola de Engenharia, Universidade Presbiteriana Mackenzie, São Paulo 01302-907, SP, Brazil.
Entropy (Basel, Switzerland)
|March 28, 2024
Summary
This study models bargaining using emotions in the Ultimatum Game. Joyful agents dominated, accumulating more wealth and promoting fairness, while other emotions led to less successful negotiations.
Area of Science:
- Behavioral Economics
- Computational Social Science
- Game Theory
Background:
- The Ultimatum Game models social bargaining.
- Agent-based models simulate complex social interactions.
- Basic emotions can influence decision-making in economic games.
Purpose of the Study:
- To evaluate agent-based strategies in a spatial Ultimatum Game.
- To determine the impact of basic emotions (anger, fear, joy, sadness, surprise) on negotiation outcomes.
- To analyze the emergence of fairness through simulations.
Main Methods:
- Agent-based modeling of a modified spatial Ultimatum Game.
- Simulation of five emotion-inspired strategies: anger, fear, joy, sadness, surprise.
- Computation of population prevalence, accumulated money, and information entropy.
Main Results:
- Joyful agents were the most prevalent and accumulated the most money.
- Simulations showed a tendency towards fairness emerging from interactions.
- Information entropy analysis revealed dynamics of population diversity and wealth distribution.
Conclusions:
- Joyful strategies appear dominant in this simulated social network.
- The spatial Ultimatum Game with emotion-based agents can lead to the emergence of fairness.
- Agent-based modeling provides insights into the evolution of social behaviors and economic decision-making.
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