1162 Open source projects that are alternatives of or similar to Rl Baselines Zoo

A collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included.

Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms

gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo

Implementation of selected reinforcement learning algorithms in Tensorflow. A3C, DDPG, REINFORCE, DQN, etc.

DrQ: Data regularized Q

A collection of multi agent environments based on OpenAI gym.

OpenAI Gym wrapper for the DeepMind Control Suite

Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotion.

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

Source codes for the book "Reinforcement Learning: Theory and Python Implementation"

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

PyTorch implementation of Deterministic Generative Adversarial Imitation Learning (GAIL) for Off Policy learning

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Explore and find reinforcement learning environments in a list of 150+ open source environments.

Sequential model-based optimization with a `scipy.optimize` interface

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

MuZero

A universal flight control tuning framework

Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

Python library for Reinforcement Learning.

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

A Trading environment base on Gym

AI research environment for the Atari 2600 games 🤖.

Run OpenAI Gym on a Server

Hyperparameter optimization in Julia.

Easy Hyper Parameter Optimization with mlr and mlrMBO.

Pytorch implementation of the PAAC algorithm presented in Efficient Parallel Methods for Deep Reinforcement Learning https://arxiv.org/abs/1705.04862

Black box hyperparameter optimization made easy.

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

A library for performing hyperparameter optimization

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros

AI Research Platform for Reinforcement Learning from Real Panoramic Images.

🦅Hyperparameter optimization for machine learning pipelines 🦅

Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes

These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.

RAD: Reinforcement Learning with Augmented Data

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

Collection of Deep Reinforcement Learning algorithms

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

ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation

Seamless, distributed, real-time integration of Blender into PyTorch data pipelines

Texas holdem OpenAi gym poker environment with reinforcement learning based on keras-rl. Includes virtual rendering and montecarlo for equity calculation.

Implementation of Inverse Reinforcement Learning (IRL) algorithms in python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL

Structural implementation of RL key algorithms

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features

A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementations with an aim to improve accessibility in RL

Proto-RL: Reinforcement Learning with Prototypical Representations

A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.

Simple 3D interior simulator for RL & robotics research

HoME: a Household Multimodal Environment is a platform for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

Self-driving car simulator for the Duckietown universe

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

Experimental Global Optimization Algorithm

S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics

AutoKernel 是一个简单易用，低门槛的自动算子优化工具，提高深度学习算法部署效率。

A3C LSTM Atari with Pytorch plus A3G design

Hearthstone simulator using C++ with some reinforcement learning

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