473 Open source projects that are alternatives of or similar to Ppo Pytorch

PyTorch implementation of some reinforcement learning algorithms: A2C, PPO, Behavioral Cloning from Observation (BCO), GAIL.

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

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

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Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch.

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

Repo for the Deep Reinforcement Learning Nanodegree program

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PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020. Please star.

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An elegant PyTorch deep reinforcement learning library.

Deep reinforcement learning using baidu PARL(maze,flappy bird and so on)

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Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

A course on Deep Reinforcement Learning in Computer Vision. Visit Website:

Highly Modular and Scalable Reinforcement Learning

Reinforcement learning tutorials

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Modularized Implementation of Deep RL Algorithms in PyTorch

Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]

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).

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TensorFlow A2C to solve Acrobot, with synchronized parallel environments

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🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework

Live Trading. Please star.

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31 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.

Deep Reinforcement Learning by using Proximal Policy Optimization and Random Network Distillation in Tensorflow 2 and Pytorch with some explanation

Mxnet implementation of Deep Reinforcement Learning papers, such as DQN, PG, DDPG, PPO

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StarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)