puyuan1996/MARL
Implementation for mSAC methods in PyTorch
This project helps AI researchers and developers working on multi-agent reinforcement learning (MARL) problems, specifically in the domain of real-time strategy games like StarCraft II. It takes a defined StarCraft II micromanagement scenario as input and outputs trained intelligent agents capable of controlling units effectively in cooperative tasks. The primary users are AI and machine learning researchers, especially those focused on multi-agent systems and game AI.
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Use this if you are an AI researcher or developer aiming to train highly effective, cooperative AI agents for complex real-time strategy game scenarios with large action spaces.
Not ideal if you are looking for a plug-and-play solution for non-game-related multi-agent problems or if you are not comfortable with deep reinforcement learning frameworks like PyTorch.
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Python
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Last pushed
Oct 10, 2021
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