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Updated: Jun 20, 2026
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Decoding Natural Behavior from Neuroethological Embedding
Published on: October 3, 2025
Decoding species coexistence: A reinforcement learning perspective
Kaiwen Jiang1, Chenyang Zhao1,2, Shengfeng Deng1
1Shaanxi Normal University, School of Physics and Information Technology, Xi'an 710061, People's Republic of China.
Physical Review. E
|June 19, 2026
Summary
Biodiversity is maintained through adaptive mobility in ecological models. Joint reinforcement learning enables species coexistence by balancing survival and predation behaviors, overcoming limitations of fixed mobility assumptions.
Area of Science:
- Ecology
- Theoretical Ecology
- Computational Ecology
Background:
- Maintaining biodiversity is a central ecological question.
- Rock-paper-scissors (RPS) game models show mobility impacts species coexistence.
- Fixed mobility assumptions in RPS models conflict with observations of mobile species coexistence.
Purpose of the Study:
- To investigate biodiversity maintenance using a spatial RPS model with adaptive mobility.
- To explore how joint reinforcement learning influences species coexistence and mobility strategies.
- To reconcile theoretical predictions with empirical observations of mobile species.
Main Methods:
- Developed a joint reinforcement learning framework for a spatial RPS model.
- Implemented a Q-learning algorithm for adaptive mobility guided by a shared Q-table.
- Analyzed behavioral tendencies (survival and predation priorities) and their impact on coexistence.
Main Results:
- Achieved stable coexistence of three species across a wide range of migration rates.
- Identified behavioral tendencies: survival priority (escaping predators) and predation priority (staying near prey).
- Demonstrated that adaptive mobility provides an evolutionary advantage over fixed mobility.
Conclusions:
- Joint reinforcement learning offers a novel approach to understanding biodiversity maintenance.
- Adaptive mobility, driven by balanced behavioral priorities, is key to stable species coexistence.
- The framework has implications for ecological theory and conservation strategy design.
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