Topic: gym-environments Goto Github
Some thing interesting about gym-environments
Some thing interesting about gym-environments
gym-environments,Repository of implementation of few algorithms for Underactuated Systems in Robotics and solutions to some interesting problems
User: aditya-shirwatkar
gym-environments,Create new gridworld gym environments easily
Organization: aig-upf
gym-environments,The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
User: aminhp
gym-environments,RL Agent for Atari Game Pong
User: amirhossein-hkh
gym-environments,Clustor deployable custom DDPG algorithm for Multi Agent RL impleted in Tensorflow
User: asokraju
gym-environments,Multi agent gym environment based on the classic Snake game with implementations of various reinforcement learning algorithms in pytorch
User: atharv24
gym-environments,Gym environments and agents for autonomous driving.
Organization: bark-simulator
Home Page: https://bark-simulator.github.io/
gym-environments,**象棋gym环境
User: bupticybee
gym-environments,Set of reinforcement learning environments for optical networks
User: carlosnatalino
gym-environments,A custom implementation of DeepMind's "the commons game"
User: danfoa
gym-environments,A collection of RL gymnasium environments for learning to grasp 3D deformable objects.
Organization: dfki-ric
gym-environments,Pytorch Implementation of MuZero for gym environment. It support any Discrete , Box and Box2D configuration for the action space and observation space.
User: dhdev0
gym-environments,Pytorch Implementation of MuZero Unplugged for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
User: dhdev0
gym-environments,Pytorch Implementation of Stochastic MuZero for gym environment. This algorithm is capable of supporting a wide range of action and observation spaces, including both discrete and continuous variations.
User: dhdev0
gym-environments,Cellular Automata Environments for Reinforcement Learning
User: elbecerrasoto
gym-environments,Documentation and ressources of Kraby, an open-source hexapod robot
User: erdnaxe
Home Page: https://kraby.readthedocs.io
gym-environments,Multi-objective Gymnasium environments for reinforcement learning
Organization: farama-foundation
Home Page: http://mo-gymnasium.farama.org/
gym-environments,A Reinforcement Learning space to test a variety of algorithms with a variety of environments, both with single and multiple agents.
User: finn1y
gym-environments,OpenAI's PPO baseline applied to the classic game of Snake
User: gniendorf
gym-environments,It is a reinforcement learning environment for block puzzle games.
User: helpingstar
gym-environments,GYM Management System
User: jehankandy
gym-environments,Gym Interface Wrapper for Simulink Models
User: johbrust
Home Page: https://quire.io/w/Simulink_Gym
gym-environments,An AI gym for building, measuring, and learning agents in massively parallel fuzzed environments using the Chinese Room Abstract Stack (Crabs) machine, ASCII Data Types, and Script2.
Organization: kabukistarship
gym-environments,A power network simulator with a Reinforcement Learning-focused usage.
User: marvinler
Home Page: https://pypownet.readthedocs.io/
gym-environments,reinforcement learning Double Deep Q Learning (DDQN) method to solve OpenAi Gym "LunarLander-v2" by usnig Double Deep NeuralNetworks
User: mohammadasadolahi
gym-environments,Implementations of a large collection of reinforcement learning algorithms.
User: natetsang
gym-environments,PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments
User: nikhilbarhate99
gym-environments,Beer Game implemented as an OpenAI gym environment.
User: orlov-ai
gym-environments,Collection of Reinforcement Learning / Meta Reinforcement Learning Environments.
Organization: paddlepaddle
gym-environments,Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:
User: praveen-palanisamy
Home Page: https://arxiv.org/abs/1911.04175
gym-environments,Partially Observable Process Gym
Organization: proroklab
Home Page: https://popgym.readthedocs.io/en/latest/
gym-environments,A toolkit for auto-generation of OpenAI Gym environments from RDDL description files.
Organization: pyrddlgym-project
Home Page: https://pyrddlgym.readthedocs.io/
gym-environments,Hosts domain and instance RDDL files, covering problems from a wide range of disciplines, integration with the pyRDDLGym ecosystem.
Organization: pyrddlgym-project
Home Page: https://pyrddlgym.readthedocs.io/en/latest/rddlrepo.html
gym-environments,A collection of Gymnasium compatible games for reinforcement learning.
User: qlan3
gym-environments,Implementation of Trust Region Policy Optimization and Proximal Policy Optimization algorithms on the objective of Robot Walk.
Organization: reinai
gym-environments,A reinforcement learning-oriented Panda Emika Franka gazebo simulation.
User: rickstaa
Home Page: https://rickstaa.dev/panda-gazebo/
gym-environments,Framework for integrating ROS and Gazebo with gymnasium, streamlining the development and training of RL algorithms in realistic robot simulations.
User: rickstaa
Home Page: https://rickstaa.dev/ros-gazebo-gym/
gym-environments,A set of practical examples showcasing the use of gymnasium environments in the ros-gazebo-gym package.
User: rickstaa
Home Page: https://rickstaa.dev/ros-gazebo-gym
gym-environments,A Catkin workspace designed to simplify the setup and use of the ROS Gazebo Gym framework.
User: rickstaa
Home Page: https://rickstaa.dev/ros-gazebo-gym/
gym-environments,This package contains several gymnasium environments with positive definite cost functions, designed for compatibility with stable RL agents.
User: rickstaa
Home Page: https://rickstaa.dev/stable-gym
gym-environments,Design Reinforcement Learning environments that model Active Network Management (ANM) tasks in electricity distribution networks.
User: robinhenry
Home Page: https://gym-anm.readthedocs.io/en/latest/
gym-environments,🎳 Environments for Reinforcement Learning
Organization: robocin
gym-environments,Grid2Op a testbed platform to model sequential decision making in power systems.
Organization: rte-france
Home Page: https://grid2op.readthedocs.io/
gym-environments,Reinforcement learning in haskell
Organization: sentenai
Home Page: https://sentenai.github.io/reinforce/
gym-environments,A repository of Q-learning based Deep Reinforcement learning algorithms, including Linear DQN, DQN with experience reply, Dueling DQN and Double Dueling DQN. Mostly tested on Gym environments.
User: shubhamag
gym-environments,An open-source framework to benchmark and assess safety specifications of Reinforcement Learning problems.
User: svengronauer
gym-environments,Relentlessly learning, persistently failing, but never surrendering.
User: tartavull
gym-environments,Repository of implementation of few algorithms for Under-actuated Systems in Robotics and solutions to some interesting problems
User: tayalmanan28
gym-environments,A toolkit for working with RDDL domains in Python3.
User: thiagopbueno
Home Page: https://rddlgym.readthedocs.io/
gym-environments,Custom environment for OpenAI gym
User: ttitcombe
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