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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
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A dynamic over games drives selfish agents to win-win outcomes
1Department of Communication, University of California Davis, One Shields Avenue, Davis, CA 95616, USA.
Proceedings. Biological Sciences
|December 16, 2020
Summary
Self-interested agents evolving within game systems spontaneously develop fair outcomes. This institutional evolution framework shows cooperation emerging without traditional mechanisms like reputation or repetition.
Area of Science:
- Social Sciences
- Game Theory
- Evolutionary Biology
Background:
- Formalisms are needed to model how agents change social systems from within.
- Distinguishing between-game 'institutional evolution' and within-game 'behavioural evolution' is crucial for understanding social dynamics.
Purpose of the Study:
- To introduce a novel framework for modeling institutional change driven by agent interactions.
- To investigate the emergent properties of games selected by self-interested agents over time.
Main Methods:
- Agents trace trajectories through a 'game space' by selecting and playing a series of games.
- Agent preferences for game features (stability, fairness, efficiency) guide navigation towards 'attractor' games.
- Computational analysis of institutional change trajectories in a two-player game space.
Main Results:
- Attractor games disproportionately exhibit fair outcomes, despite agents being strictly self-interested.
- Fairness emerges because it co-occurs with self-serving features preferred by agents.
- Institutional evolution promotes cooperation among selfish agents without relying on space, reputation, or repetition.
Conclusions:
- Institutional evolution offers a mechanism for the spontaneous emergence of cooperation in self-interested agent groups.
- The framework provides a flexible model for interdependencies between behavioral and institutional evolutionary processes.
- This research contributes to understanding the evolution of cooperation in social systems.
Keywords:
behavioural ecologybiological institutionscultural evolutionevolution of cooperationnumerical simulationMore Related Videos
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