Mava: a scalable, research framework for multi-agent reinforcement learning
The framework integrates with popular MARL environments such as PettingZoo, SMAC, RoboCup, OpenSpiel, Flatland , as well as a few custom environments.
Mava includes distributed implementations of multi-agent versions of ddpg, d4pg, dqn, ppo, as well as DIAL, VDN and QMIX.
ArXiV: https://arxiv.org/pdf/2107.01460.pdf
GitHub: https://github.com/instadeepai/Mava
#MARL #RL #dl
The framework integrates with popular MARL environments such as PettingZoo, SMAC, RoboCup, OpenSpiel, Flatland , as well as a few custom environments.
Mava includes distributed implementations of multi-agent versions of ddpg, d4pg, dqn, ppo, as well as DIAL, VDN and QMIX.
ArXiV: https://arxiv.org/pdf/2107.01460.pdf
GitHub: https://github.com/instadeepai/Mava
#MARL #RL #dl
GitHub
GitHub - instadeepai/Mava: 🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX - instadeepai/Mava