There are 7 repositories under ppo topic.
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
强化学习中文教程(蘑菇书🍄),在线阅读地址:https://datawhalechina.github.io/easy-rl/
Repo for the Deep Reinforcement Learning Nanodegree program
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
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).
Massively Parallel Deep Reinforcement Learning. 🔥
Modularized Implementation of Deep RL Algorithms in PyTorch
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
For trading. Please star.
Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
This is the official implementation of Multi-Agent PPO (MAPPO).
PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
Clean, Robust, and Unified PyTorch implementation of popular DRL Algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
A simple and well styled PPO implementation. Based on my Medium series: https://medium.com/@eyyu/coding-ppo-from-scratch-with-pytorch-part-1-4-613dfc1b14c8.
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.
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
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.
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Really Fast End-to-End Jax RL Implementations
A library with extensible implementations of DPO, KTO, PPO, ORPO, and other human-aware loss functions (HALOs).
PyTorch C++ Reinforcement Learning
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
PyTorch implementation of deep reinforcement learning algorithms
Long-Term Evolution Project of Reinforcement Learning
RAD: Reinforcement Learning with Augmented Data