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Evolution of cooperative strategies from first principles
Mikhail Burtsev1, Peter Turchin
1Department of Non-linear Dynamics, Keldysh Institute of Applied Mathematics of RAS, Moscow 125047, Russia. mbur@narod.ru
Cooperative behavior can evolve in simulations when agents can perceive external markers of others. This study models complex strategies, showing cooperation emerges from simple rules and evolution.
Area of Science:
- Evolutionary biology
- Social sciences
- Game theory
Background:
- Understanding the evolution of cooperative behavior is a major challenge in biological and social sciences.
- Existing theories include kin selection, reciprocity, and multilevel selection.
- Game theory, particularly agent-based simulations, is a key tool for analyzing cooperation.
Purpose of the Study:
- To test evolutionary game theory with a more complex model.
- To explore the emergence of cooperative strategies from elementary actions and a neural net.
- To investigate the conditions under which cooperation can evolve.
Main Methods:
- Developed a computer model with agents possessing limited receptors and elementary actions.
- Allowed evolution to construct strategies from these components, rather than predetermining them.
- Simulated interactions to observe emergent behavioral strategies.
Main Results:
- The model successfully evolved well-known strategies like dove, hawk, and bourgeois.
- Two novel cooperative strategies, cooperative attack and defense, emerged from the simulations.
- Cooperative strategies evolved under minimalist assumptions when agents could perceive heritable external markers.
Conclusions:
- Cooperative behaviors can evolve even with simple agent structures and learning capabilities.
- The ability to perceive external markers is crucial for the evolution of cooperation.
- This model provides a more stringent test of game-theoretic explanations for cooperation.
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