oxwhirl/smac
SMAC: The StarCraft Multi-Agent Challenge
This project helps AI researchers and academics working on multi-agent reinforcement learning (MARL) to test and develop their algorithms. It provides a standardized environment using Blizzard's StarCraft II game, specifically focusing on scenarios where individual units are controlled by separate AI agents. Researchers can input their MARL algorithms and receive battle outcomes and agent behaviors within these complex real-time strategy settings.
1,330 stars. No commits in the last 6 months.
Use this if you are developing or evaluating cooperative multi-agent reinforcement learning algorithms and need a challenging, decentralized micromanagement testbed.
Not ideal if you are a StarCraft II player looking for AI opponents or a game developer wanting to integrate general AI into your game.
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1,330
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Language
Python
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MIT
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Last pushed
Feb 18, 2024
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