A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
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Back-end Developer Contributions:15 commits, 1 PR, 7 pushes in 2 days
Contributions summary:Paaras primarily contributed to the development of environments within the pettingzoo library, focusing on the integration of new observation spaces and action masks, specifically within the classic environments for games like Tic Tac Toe, Connect Four, Backgammon, Checkers, Hanabi, Go, Texas Hold'em, and Chess. The user implemented these changes by modifying the observation spaces to include dictionary-based formats with 'observation' and 'action_mask' keys. These modifications likely aimed to improve the compatibility of these environments with reinforcement learning algorithms and frameworks.
multi-agent-reinforcement-learningapigymnasiumreinforcement-learningmultiagent-reinforcement-learning
Contributions:2 PRs, 192 pushes, 4 branches in 7 years 6 months