rlax

geek-ai/magent1.7K

RL platform

A platform for multi-agent reinforcement learning research and development

google-research/deep_ope85

RL benchmarks

Provides benchmarking policies and datasets for offline reinforcement learning

aunum/gold345

RL library

A reinforcement learning library for Go, providing a set of agents to solve challenges in various environments.

eleurent/rl-agents596

RL frameworks

A collection of implementations of Reinforcement Learning and planning algorithms in Python.

rll-research/url_benchmark335

RL Benchmark

A benchmark suite for unsupervised reinforcement learning agents, providing pre-trained models and scripts for testing and fine-tuning agent performance.

luchris429/purejaxrl755

RL framework

A high-performance implementation of reinforcement learning training pipelines using JAX and PyTorch-like functionality

mushroomrl/mushroom-rl824

RL library

A Python library for reinforcement learning algorithms and environments.

kaixhin/rainbow1.6K

RL framework

A Python implementation of a deep reinforcement learning algorithm combining multiple techniques for improved performance in Atari games

rlworkgroup/garage1.9K

RL toolkit

A toolkit for developing and evaluating reinforcement learning algorithms in a reproducible manner

chainer/chainerrl1.2K

RL library

A deep reinforcement learning library built on top of Chainer.

enlite-ai/maze266

RL Framework

An RL framework for building and training reinforcement learning models in Python

devendrachaplot/deeprl-grounding237

RL Agent Trainer

Trains an RL agent to execute natural language instructions in a 3D environment using a combination of A3C and gated attention mechanisms.

roberttlange/gymnax669

RL accelerator

A framework that accelerates RL environment processes by leveraging JAX and GPU acceleration

matthiasplappert/keras-rl8

RL framework

A Python library implementing state-of-the-art deep reinforcement learning algorithms for Keras and OpenAI Gym environments.

alex-petrenko/sample-factory839

RL library

A high-throughput reinforcement learning library with optimized synchronous and asynchronous implementations of policy gradients.