MARL @ SJTU

Multi-Agent Research at Shanghai Jiao Tong University

Shanghai, China

Pinned Repositories

bd_rd_psro
Code for Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
Language:Python19 2 03
Competition_Olympics-Running
Olympics-Running Env based on Jidi
Language:Python0 0 01
dm_control
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Language:Python0 0 00
GTML22_baseline
SJTU course AI3617
Language:Python1 7 01
malib
A parallel framework for population-based multi-agent reinforcement learning.
Language:Python494 9 3659
multiagent-particle-envs
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
Language:Python00
RLApps
RLlib-based general reinforcement learning algorithm collections
Language:Python1 0 00
seed_rl
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
Language:Python2 1 00
ZSC-Eval
This repository is the official implementation of ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination. Pre-trained Agent Zoo: https://huggingface.co/Leoxxxxh/ZSC-Eval-policy_pool.
Language:JavaScript26 3 04

sjtu-marl/malib
A parallel framework for population-based multi-agent reinforcement learning.
Language:Python494 9 3659
sjtu-marl/ZSC-Eval
This repository is the official implementation of ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination. Pre-trained Agent Zoo: https://huggingface.co/Leoxxxxh/ZSC-Eval-policy_pool.
Language:JavaScript26 3 04
sjtu-marl/bd_rd_psro
Code for Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
Language:Python19 2 03
sjtu-marl/seed_rl
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
Language:Python2 1 00
sjtu-marl/GTML22_baseline
SJTU course AI3617
Language:Python1 7 01
sjtu-marl/RLApps
RLlib-based general reinforcement learning algorithm collections
Language:Python1 0 00
sjtu-marl/Competition_Olympics-Running
Olympics-Running Env based on Jidi
Language:Python0 0 01
sjtu-marl/dm_control
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Language:Python0 0 00
sjtu-marl/multiagent-particle-envs
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
Language:Python00