Pinned Repositories
Distributional-Multi-Agent-Actor-Critic-Reinforcement-Learning-MADDPG-Tennis-Environment
The state-of-the-art in multi-agent Reinforcement Learning is the MADDPG algorithm which utilises DDPG actor-critic neural networks where each agent uses centralized critic training but decentralized actor execution, and is capable of learning either cooperative or competitive environments. This is demonstrated on the Unity Tennis Environment.
JD_MADDPG
JD_MADDPG_10agents
JD_MADDPG_6agents
RGMComm
SARNet
JingdiC's Repositories
JingdiC/SARNet
JingdiC/Distributional-Multi-Agent-Actor-Critic-Reinforcement-Learning-MADDPG-Tennis-Environment
The state-of-the-art in multi-agent Reinforcement Learning is the MADDPG algorithm which utilises DDPG actor-critic neural networks where each agent uses centralized critic training but decentralized actor execution, and is capable of learning either cooperative or competitive environments. This is demonstrated on the Unity Tennis Environment.
JingdiC/JD_MADDPG
JingdiC/JD_MADDPG_10agents
JingdiC/JD_MADDPG_6agents
JingdiC/RGMComm