#Actor-critic
Showing 22 of 22 repositories tagged #actor-critic, ranked by stars
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
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).
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
Minimal and Clean Reinforcement Learning Examples
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Deep Reinforcement Learning with pytorch & visdom
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
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)
Simple A3C implementation with pytorch + multiprocessing
PyTorch implementation of Soft Actor-Critic (SAC)
Reaver: Modular Deep Reinforcement Learning Framework. Focused on StarCraft II. Supports Gym, Atari, and MuJoCo.
Reinforcement learning framework to accelerate research
Code for our paper "Visualizing and Understanding Atari Agents" (https://goo.gl/AMAoSc)
A comprehensive guide to Reinforcement Learning
Explorer is a PyTorch reinforcement learning framework for exploring new ideas.
JAX implementations of core Deep RL algorithms
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
Algorithmic trading using heterogeneous graph neural network and reinforcement learning, pre-alpha
Deep Reinforcement Learning for Trading