A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities

Octo is a transformer-based robot policy trained on a diverse mix of 800k robot trajectories.

Python interface for accessing the near real-world offline reinforcement learning (NeoRL) benchmark datasets

detectron2 windows build

Beautiful charts for iOS/tvOS/OSX! The Apple side of the crossplatform MPAndroidChart.

CSV parser for Swift

Code for "Gradient Surgery for Multi-Task Learning"

Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

Python package that implements Continuous Time Recurrent Neural Networks (CTRNNs)

Code Repository for Liquid Time-Constant Networks (LTCs)

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3 BC, LB-SAC, SPOT, Cal-QL, ReBRAC

Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/

Conservative Q Learning on top of SAC

Robotics Gym Environments

Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.

Multi-objective Gymnasium environments for reinforcement learning

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

Code for conservative Q-learning

An educational resource to help anyone learn deep reinforcement learning.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

Collection of reinforcement learning algorithms

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning

A collection of robotics simulation environments for reinforcement learning