An elegant PyTorch deep reinforcement learning library.
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Updated
Aug 5, 2024 - Python
An elegant PyTorch deep reinforcement learning library.
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
Python library for Reinforcement Learning.
Reinforcement learning algorithms for MuJoCo tasks
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.
PyTorch implementation of Trust Region Policy Optimization
A unified framework for robot learning
A collection of robotics simulation environments for reinforcement learning
Unified Reinforcement Learning Framework
This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.
PyTorch Implementation of REINFORCE for both discrete & continuous control
[CoRL '23] Dexterous piano playing with deep reinforcement learning.
DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)
PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)
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