Pinned Repositories
jquery
jQuery JavaScript Library
metarl
Meta RL Project
mujoco-py
MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.
niugit
paper
Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials
RL-Adventure-2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
RODE
Codes accompanying the paper "RODE: Learning Roles to Decompose Multi-Agent Tasks (ICLR 2021, https://arxiv.org/abs/2010.01523). RODE is a scalable role-based multi-agent learning method which effectively discovers roles based on joint action space decomposition according to action effects, establishing a new state of the art on the StarCraft multi-agent benchmark.
ROMA
Codes accompanying the paper "ROMA: Multi-Agent Reinforcement Learning with Emergent Roles" (ICML 2020 https://arxiv.org/abs/2003.08039)
tensorlayer
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
niuliyuan's Repositories
niuliyuan/jquery
jQuery JavaScript Library
niuliyuan/metarl
Meta RL Project
niuliyuan/mujoco-py
MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.
niuliyuan/niugit
niuliyuan/paper
niuliyuan/Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials
niuliyuan/RL-Adventure-2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
niuliyuan/RODE
Codes accompanying the paper "RODE: Learning Roles to Decompose Multi-Agent Tasks (ICLR 2021, https://arxiv.org/abs/2010.01523). RODE is a scalable role-based multi-agent learning method which effectively discovers roles based on joint action space decomposition according to action effects, establishing a new state of the art on the StarCraft multi-agent benchmark.
niuliyuan/ROMA
Codes accompanying the paper "ROMA: Multi-Agent Reinforcement Learning with Emergent Roles" (ICML 2020 https://arxiv.org/abs/2003.08039)
niuliyuan/tensorlayer
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥