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#计算机科学#Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
Reinforcement learning baseline agent trained with the Actor-critic (A3C) algorithm.
This repository contains the code to implement the Hierarchical Actor-Critic (HAC) algorithm.
The source code for "An Actor Critic Algorithm for Structured Prediction"
#计算机科学#Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
Pytorch implementation of the MARL algorithm, MADDPG, which correspondings to the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments".
#计算机科学#Actor-critic with experience replay
PyTorch implementation of soft actor critic
#计算机科学#PyTorch implementation of Soft Actor-Critic (SAC)
Trading with recurrent actor-critic reinforcement learning
PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..
#计算机科学#PyTorch implementation of Advantage Actor-Critic (A2C)
DSAC-v2; DSAC-T; DASC; Distributional Soft Actor-Critic
#计算机科学#PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)
General implementation of Advantage Actor Critic using Pytorch
advantage actor-critic reinforcement learning for openai gym cartpole
PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments
Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019