An elegant PyTorch deep reinforcement learning library.

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 ....

Minimal and Clean Reinforcement Learning Examples

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Scalable, event-driven, deep-learning-friendly backtesting library

Deep Reinforcement Learning For Sequence to Sequence Models

A curated list of Monte Carlo tree search papers with implementations.

A simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

Structural implementation of RL key algorithms

DEEp Reinforcement learning framework

Implementations of Reinforcement Learning Models in Tensorflow

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

Reinforcement learning tutorials

[파이썬과 케라스로 배우는 강화학습] 예제

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

EvoRL is a fully GPU-accelerated framework for Evolutionary Reinforcement Learning, implemented with JAX. It supports Reinforcement Learning (RL), Evolutionary Computation (EC), Evolution-guided Reinforcement Learning (ERL), AutoRL, and seamless integration with GPU-optimized simulation environments.