Topic: gym Goto Github
Some thing interesting about gym
Some thing interesting about gym
gym,gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo
Organization: acutronicrobotics
Home Page: https://acutronicrobotics.com
gym,Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
Organization: agilerl
Home Page: https://agilerl.com
gym,A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
User: araffin
Home Page: https://stable-baselines.readthedocs.io/
gym,S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics
User: araffin
Home Page: https://s-rl-toolbox.readthedocs.io
gym,PyTorch Implementation of REINFORCE for both discrete & continuous control
User: chingyaoc
gym,A simple, easy, customizable Gymnasium environment for trading.
User: clementperroud
Home Page: https://gym-trading-env.readthedocs.io/
gym,Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
Organization: deepdrive
Home Page: https://deepdrive.io
gym,DrQ: Data regularized Q
User: denisyarats
Home Page: https://sites.google.com/view/data-regularized-q
gym,PyTorch implementation of Soft Actor-Critic (SAC)
User: denisyarats
gym,A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Organization: dlr-rm
Home Page: https://rl-baselines3-zoo.readthedocs.io
gym,PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Organization: dlr-rm
Home Page: https://stable-baselines3.readthedocs.io
gym,Extensible Combinatorial Optimization Learning Environments
Organization: ds4dm
Home Page: https://www.ecole.ai
gym,An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
Organization: farama-foundation
Home Page: https://gymnasium.farama.org
gym, Simple and easily configurable grid world environments for reinforcement learning
Organization: farama-foundation
Home Page: https://minigrid.farama.org/
gym,An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Organization: farama-foundation
Home Page: https://pettingzoo.farama.org
gym,Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)
User: germain-hug
gym,AI research environment for the Atari 2600 games 🤖.
User: gsurma
Home Page: https://gsurma.github.io
gym,JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
User: ikostrikov
gym,Repository for Open Source Reinforcement Learning Framework JORLDY
Organization: kakaoenterprise
gym,A collection of multi agent environments based on OpenAI gym.
User: koulanurag
Home Page: https://github.com/koulanurag/ma-gym/wiki
gym,👨💻 Gym & Club Management System https://gymie.in
Organization: lubusin
gym,Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.
User: lucasalegre
Home Page: https://lucasalegre.github.io/sumo-rl
gym,Structural implementation of RL key algorithms
User: medipixel
Home Page: https://www.medipixel.io/
gym,Simple A3C implementation with pytorch + multiprocessing
User: morvanzhou
Home Page: https://mofanpy.com
gym,Sokoban environment for OpenAI Gym
User: mpschrader
gym,This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
User: navneet-nmk
gym,[ICLR 2023] Come & try Decision-Intelligence version of "Agar"! Gobigger could also help you with multi-agent decision intelligence study.
Organization: opendilab
Home Page: https://gobigger.readthedocs.io/en/latest/
gym,[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios
Organization: opendilab
Home Page: https://huggingface.co/spaces/OpenDILabCommunity/ZeroPal
gym,Unified Reinforcement Learning Framework
Organization: openrl-lab
Home Page: https://openrl-docs.readthedocs.io
gym,VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
Organization: proroklab
Home Page: https://vmas.readthedocs.io
gym,RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).
Organization: rle-foundation
Home Page: https://docs.rllte.dev/
gym,Long-Term Evolution Project of Reinforcement Learning
Organization: rle-foundation
Home Page: https://docs.rllte.dev/
gym,C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Organization: sail-sg
Home Page: https://envpool.readthedocs.io
gym,A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementations with an aim to improve accessibility in RL
Organization: sforaidl
Home Page: https://genrl.readthedocs.io
gym,Mirror of Stable-Baselines: a fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Organization: stable-baselines-team
Home Page: https://github.com/hill-a/stable-baselines
gym,Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code
Organization: stable-baselines-team
Home Page: https://sb3-contrib.readthedocs.io
gym,Reinforcement Learning Algorithms Based on PyTorch
User: stepneverstop
Home Page: https://stepneverstop.github.io
gym,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
Organization: tinkoff-ai
Home Page: https://arxiv.org/abs/2210.07105
gym,Modular reinforcement learning library (on PyTorch and JAX) with support for NVIDIA Isaac Gym, Omniverse Isaac Gym and Isaac Lab
User: toni-sm
Home Page: https://skrl.readthedocs.io/
gym,PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
Organization: utiasdsl
Home Page: https://utiasDSL.github.io/gym-pybullet-drones/
gym,PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
Organization: utiasdsl
Home Page: https://www.dynsyslab.org/safe-robot-learning/
gym,Play games without touching keyboard
User: uvipen
gym,Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
User: uvipen
gym,Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
User: uvipen
gym,High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
User: vwxyzjn
Home Page: http://docs.cleanrl.dev
gym,Flutter fitness/workout app for wger
Organization: wger-project
gym,Self hosted FLOSS fitness/workout, nutrition and weight tracker
Organization: wger-project
Home Page: https://wger.de
gym,Unreal environments for reinforcement learning
User: zfw1226
gym,Source codes for the book "Reinforcement Learning: Theory and Python Implementation"
User: zhiqingxiao
Home Page: https://zhiqingxiao.github.io/rl-book
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