MARL-Algorithms
Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
Implement and test various multi-agent reinforcement learning algorithms in a gaming scenario.
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Free · no card · unsubscribe anytimeImplementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
MARL-Algorithms has 1.8k stars on GitHub. It has been forked 303 times. MARL-Algorithms is written mainly in Python. It has been in active development since 2019. Its main topics are deep-reinforcement-learning, multi-agent-reinforcement-learning, reinforcement-learning.
What is MARL-Algorithms?
Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
Is MARL-Algorithms open source?
MARL-Algorithms is an open-source project.
Is MARL-Algorithms free?
Yes. MARL-Algorithms is free and open source — you can use, modify and self-host it.
What language is MARL-Algorithms written in?
MARL-Algorithms is written mainly in Python.
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