Repository navigation
soft-actor-critic
- Website
- Wikipedia
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.
PyTorch implementation of soft actor critic
JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)
A PyTorch library for building deep reinforcement learning agents.
Reinforcement Learning for real-time applications - host of the TrackMania Roborace League
PyTorch implementation of Soft Actor-Critic (SAC)
深度强化学习路径规划, SAC-Auto路径规划, Soft Actor-Critic算法, SAC-pytorch，激光雷达Lidar避障，激光雷达仿真模拟，Adaptive-SAC
RAD: Reinforcement Learning with Augmented Data
lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
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 and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.
PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)
A pytorch tutorial for DRL(Deep Reinforcement Learning)
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
JAX implementation of deep RL agents with resets from the paper "The Primacy Bias in Deep Reinforcement Learning"
Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC