#Soft-actor-critic
Showing 11 of 11 repositories tagged #soft-actor-critic, ranked by stars
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
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)
PyTorch implementation of Soft Actor-Critic (SAC)
lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
Modified versions of the SAC algorithm from spinningup for discrete action spaces and image observations.
Proto-RL: Reinforcement Learning with Prototypical Representations
JAX implementations of core Deep RL algorithms
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
ReinforceUI-Studio. A Python-based application designed to simplify the configuration and monitoring of RL training processes. Supporting MuJoCo, OpenAI Gymnasium, and DeepMind Control Suite. Algorithms included: CTD4, DDPG, DQN, PPO, SAC, TD3, TQC