An elegant PyTorch deep reinforcement learning library.
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Updated
Sep 10, 2024 - Python
An elegant PyTorch deep reinforcement learning library.
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version
Python library for Reinforcement Learning.
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
Implementation of papers in 100 lines of code.
A curated list of Monte Carlo tree search papers with implementations.
📘 The experiment tracker for foundation model training
Implementation of Inverse Reinforcement Learning (IRL) algorithms in Python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Omniverse Isaac Gym and Isaac Lab
Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo
A universal flight control tuning framework
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