Benchmark Results

Comprehensive MARL Algorithm Evaluation on Coopetition-Gym

Comprehensive benchmarks comparing multi-agent reinforcement learning algorithms across all 20 Coopetition-Gym environments are forthcoming. Results will include algorithm rankings, environment-specific analysis, trust dynamics validation, and research insights upon publication of the accompanying scientific research paper.

For questions about benchmarks, please contact the authors.

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Citation

@software{coopetition_gym,
  title = {Coopetition-Gym: Environments for Mixed-Motive Multi-Agent Reinforcement Learning},
  author = {Pant, Vik and Yu, Eric},
  year = {2026},
  institution = {Faculty of Information and Department of Computer Science, University of Toronto}
}