Reverse Dependencies of gym

The following projects have a declared dependency on gym:

• 3d-connectX-env — 3D ConnectX for OpenAI Gym.
• a2rl — Make recommendations for sequential decision problems using offline data
• abmarl — Agent Based Simulation and MultiAgent Reinforcement Learning
• active-pre-train-ppg — Unsupervised pre-training with PPG
• adeptRL — Reinforcement Learning Framework
• adversarial-gym — OpenAI Gym environments for adversarial games for the operation beat ourselves organisation.
• affordable — Affordable is an abstraction layer to facilitate RL environment developing
• agents-bar — A client to work with Agents Bar (https://agents.bar).
• agnes — AGNES - Flexible Reinforcement Learning Framework with PyTorch
• agymc — A concurrent wrapper for OpenAI Gym library that runs multiple environments concurrently.
• AI-envs — Ambientes do gym
• ai-projects — Collection of AI algorithms and agents.
• ai-traineree — Yet another zoo of (Deep) Reinforcment Learning methods in Python using PyTorch
• aicrowd-gym — A gym wrapper for RL evaluations on AIcrowd
• aideml — Autonomous AI for Data Science and Machine Learning
• aigar — Gym-compatible environments that replicate the aigar.io game to a certain extent.
• aine-drl — AINE-DRL is a deep reinforcement learning (DRL) baseline framework. AINE means "Agent IN Environment".
• airdeploy — RLEF
• airgym — OpenAI Gym environment for training reinforcement learning agents on an XPlane simulator
• airinfer — RLEF
• airscale — RLEF
• airtrain — RLEF
• all-params-env — A 0penAI Gym Env for Lsm
• alt-gym-wordle — OpenAI gym environment for training agents on Wordle
• android-env — AndroidEnv environment and library for training agents.
• anvil-rl — Adaptable tools to make reinforcement learning algorithms
• anvilrl — Adaptable tools to make reinforcement learning algorithms
• anyrl — A library for Reinforcement Learning
• apropos-ai — Learning algorithms for production language model programs
• aquacropgym — openai-gym crop simulation environment
• arlie — Agent of Reinforcement Learning for Intelligent Environments
• AssetAllocator — Train RL agents to manage a portfolio
• ast-toolbox — A toolbox for worst-case validation of autonomous policies
• autonomous-learning-library — A library for building reinforcement learning agents in Pytorch
• avalanche-lib — Avalanche: a Comprehensive Framework for Continual Learning Research
• avalon-rl — Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds
• baconian — model-based reinforcement learning toolbox
• bahiart-gym — A toolkit to develop openAI Gym environments on top of the RCSSSERVER3D simulator
• balrog-nle — BALROG version of The NetHack Learning Environment (NLE)
• barbell — A tool for creating Gym environments
• bark-ml — Gym Environments and Agents for Autonomous Driving
• bauwerk — Simple building control environments for reinforcement learning.
• bbrl-gym — A set of additional gym environments
• bci-feedback — GCPDS: Scripts for test BCI with Pacman.
• bellman — A Toolbox for Model-Based Reinforcement Learning in TensorFlow
• beobench — Beobench is a toolkit providing easy and unified access to building control environments for reinforcement learning (RL).
• betting-env — Create a custom GYM environment to simulate trading strategy.
• bidexhands — Benchmark environments for Dexterous Hand in NVIDIA IsaacGym.
• bindsnet — Spiking neural networks for ML in Python
• bipedal-skills — Bipedal Skills RL Benchmark
• blackbox-mpc — BlackBox MPC - Model Predictive Control withsampling based optimizers
• blackhc.mdp — MDP framework for the OpenAI Gym
• blokus-gym — OpenAI gym environment for Blokus
• bluesky-cartpole — Train a cartpole agent with bluesky and ophyd!
• boardgame2 — 2-player zero-sum board game extension for OpenAI Gym.
• bonsai-gym — A python library for integrating Bonsai BRAIN with Open AI Gym environments.
• bonsai-gym-common — A library to integrate Bonsai BRAIN with OpenAI Gym environments
• bounded-prescience — Shielding Atari Games with Bounded Prescience
• brax — A differentiable physics engine written in JAX.
• briscola-gym — Gym environment for Briscola game
• bullet-gym — A OpenAI Gym Env for pandas
• bullet-ur-gym-test — An OpenAI Gym Env for UR
• captain-project — Conservation Area Prioritization Through Artificial INtelligence
• carl-bench — CARL- Contextually Adaptive Reinforcement Learning
• cartpole — no summary
• catalyst-rl — Catalyst.RL. PyTorch framework for RL research.
• catratenvironment — no summary
• causal-world — CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning
• causalenv — no summary
• cfrl — no summary
• change-analyzer — Change analyzer
• ChefsHatGym — A python interface for training Reinforcement Learning agents to play the Chef's Hat Card Game.
• chi — no summary
• circrl — Tools for applying circuits-style interpretability techniques to RL agents.
• circuitgym — OpenAI-gym -like environments for spice circuits
• cleanrl — High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features
• clubs-gym — clubs is an open ai gym environment for running arbitrary poker configurations.
• code-rl — Code RL
• CoderSchoolAI — A Comprehensive Python Library for Creating and Developing Agent AIs.
• Colosseum-client — no summary
• comaze-gym — OpenAI Gym-compatible implementation of the game CoMaze to benchmark AI on Zero-Shot Emergent Coordination and Communication.
• commonroad-rl — Tools for applying reinforcement learning on commonroad scenarios.
• conformer-rl — Deep Reinforcement Library for Conformer Generation
• continuous-grid-world — Grid World with continuous action spaces
• coopihc — Two-agent component-based interaction environments for computational HCI with Python
• covid-env-biggreen-xprize — no summary
• crenv — RL Environment for Cryptocurrency Research
• crowdplay-datasets — A collection of crowdsourced human demonstration datasets for offline learning
• cryptogym — CryptoCurrency Trading environment
• cyberbattle — Cyber environment in Python with gym like API
• cybergenetics — Cybergenetics is a controlled simulating environment for chemical reaction networks (CRNs) and co-cultures.
• cyberrl — CyberRL
• d3rlpy — An offline deep reinforcement learning library
• DDPG-TF — DDPG implimentaion in Tensorflow-2.0
• ddpg-tf2 — Simple yet effective DDPG implementation for continuous action space,
• decuen — Reinforcement learning framework built in modern Python for experimentation, ease-of-use, modularity, and extensibility.
• deep-rl — no summary
• deep-sea-treasure — An environment for testing multi-objective reinforcement learning algorithms.
• deepair — PyTorch implementations of Deep reinforcement learning algorithms.
• deepbots — A wrapper framework for Reinforcement Learning in Webots simulator