opendilab/Gobigger-Explore
Still struggling with the high threshold or looking for the appropriate baseline? Come here and new starters can also play with your own multi-agents!
This is a codebase for exploring multi-agent reinforcement learning within the GoBigger simulation environment. It takes different training configurations as input to simulate how multiple AI agents interact and learn in a cooperative-competitive setting. The output includes performance evaluations of these agents against bots or other agents, often visualized as gameplay. It's intended for AI researchers, game AI developers, or anyone experimenting with multi-agent systems.
182 stars. No commits in the last 6 months.
Use this if you are an AI researcher or developer looking to train and evaluate various multi-agent reinforcement learning algorithms within a complex, interactive simulation.
Not ideal if you are looking for a plug-and-play solution for general game AI without diving into the specifics of reinforcement learning models.
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Language
Python
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Last pushed
Feb 20, 2023
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