422 Open source projects that are alternatives of or similar to Rainy

Modularized Implementation of Deep RL Algorithms in PyTorch

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An elegant PyTorch deep reinforcement learning library.

juliareinforcementlearning.org/

Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

Lightweight deep RL Libraray for continuous control.

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

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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)

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

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

A PyTorch library for building deep reinforcement learning agents.

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

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.

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

Repo for the Deep Reinforcement Learning Nanodegree program

TD3, SAC, IQN, Rainbow, PPO, Ape-X and etc. in TF1.x

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

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).

No description or website provided.

This Repository contains a series of google colab notebooks which I created to help people dive into deep reinforcement learning.This notebooks contain both theory and implementation of different algorithms.

Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.

A pytorch tutorial for DRL(Deep Reinforcement Learning)

RLgraph: Modular computation graphs for deep reinforcement learning

Live Trading. Please star.

Ape-X DQN & DDPG with pytorch & tensorboard

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

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Provide full reinforcement learning benchmark on mujoco environments, including ddpg, sac, td3, pg, a2c, ppo, library

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

Pytorch Implementation of Reinforcement Learning Algorithms ( Soft Actor Critic(SAC)/ DDPG / TD3 /DQN / A2C/ PPO / TRPO)

Python library for Reinforcement Learning.

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

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

JAX implementations of core Deep RL algorithms

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

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

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

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

🤖 Implements of Reinforcement Learning algorithms.

Simple (but often Strong) Baselines for POMDPs in PyTorch - ICML 2022

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

Explorer is a PyTorch reinforcement learning framework for exploring new ideas.

Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch

playing idealized trading games with deep reinforcement learning

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An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.

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Minimal implementations of reinforcement learning algorithms by Tensorflow

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient - 7th ICML AutoML workshop 2020

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

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

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow