1127 Open source projects that are alternatives of or similar to Minimalrl

This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.

Learning Continuous Control in Deep Reinforcement Learning

Deep Reinforcement Learning in Autonomous Driving: the A3C algorithm used to make a car learn to drive in TORCS; Python 3.5, Tensorflow, tensorboard, numpy, gym-torcs, ubuntu, latex

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

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators.

Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving

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

JAX implementations of core Deep RL algorithms

Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

Reinforcement learning with tensorflow 2 keras

The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)

PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments

An implementation of (Double/Dueling) Deep-Q Learning to play Super Mario Bros.

TensorFlow and Deep Learning Tutorials

StarCraft II - pysc2 Deep Reinforcement Learning Examples

Reinforcement learning environments with musculoskeletal models

PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.

My experimentations with Reinforcement Learning in Pytorch

Trax — Deep Learning with Clear Code and Speed

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

A high-performance Atari A3C agent in 180 lines of PyTorch

Reinforcement learning models in ViZDoom environment

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

Autonomous Drifting using Reinforcement Learning

Tensorforce: a TensorFlow library for applied reinforcement learning

PyTorch implementation of soft actor critic

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

Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...

Neural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.

MXNET + OpenAI Gym implementation of A3C from "Asynchronous Methods for Deep Reinforcement Learning"

Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

Reinforcement Learning Algorithms

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

PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code

Structural implementation of RL key algorithms

ChainerRL is a deep reinforcement learning library built on top of Chainer.

Master Thesis: Limit order placement with Reinforcement Learning

Implementation of the algorithm in Python 3, TensorFlow and OpenAI Gym

Using deep reinforcement learning to tackle the game 2048.

use AI to play some games.

Deep Recurrent Q-Learning vs Deep Q Learning on a simple Partially Observable Markov Decision Process with Minecraft

Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.

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

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

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

A High Level Python Deep Reinforcement Learning library. Great for beginners, prototyping and quickly comparing algorithms

For deep RL and the future of AI.

Implementation of the Deep Q-learning algorithm to solve MDPs

Guided Policy Search

Asynchronous Methods for Deep Reinforcement Learning

Playing Atari games with TensorFlow implementation of Asynchronous Deep Q-Learning

PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch

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

MIT DeepTraffic top 2% solution (75.01 mph) 🚗.

Reproducing MuJoCo benchmarks in a modern, commercial game /physics engine (Unity + PhysX).

OpenAI's cartpole env solver.

Our NIPS 2017: Learning to Run source code