There are 11 repositories under gym-environment topic.
A minimalist environment for decision-making in autonomous driving
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow
Reinforcement Learning environments based on the 1993 game Doom :godmode:
Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotion.
Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
Texas holdem OpenAi gym poker environment with reinforcement learning based on keras-rl. Includes virtual rendering and montecarlo for equity calculation.
Obstacle Tower Environment
Framework for Multi-Agent Deep Reinforcement Learning in Poker
A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.
Gym Electric Motor (GEM): An OpenAI Gym Environment for Electric Motors
PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments
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.
A simple, easy, customizable Gymnasium environment for trading.
A Gym-like environment for Reinforcement Learning in Rocket League
Lightweight multi-agent gridworld Gym environment
A large-scale benchmark for co-optimizing the design and control of soft robots, as seen in NeurIPS 2021.
A python package for modelling locomotion in complex environments and spatially/velocity selective cell activity.
POGEMA stands for Partially-Observable Grid Environment for Multiple Agents. This is a grid-based environment that was specifically designed to be flexible, tunable and scalable. It can be tailored to a variety of PO-MAPF settings.
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
A gym environment for a miniature racecar using the pybullet physics engine.
OpenAI Gym Environment API based Bitcoin trading environment
An API conversion tool for popular external reinforcement learning environments
An OpenAI Gym environment for the Flappy Bird game
深度强化学习路径规划, SAC-Auto路径规划, Soft Actor-Critic算法, SAC-pytorch,激光雷达Lidar避障,激光雷达仿真模拟,Adaptive-SAC
An OpenAI Gym environment wrapper for the Mupen64Plus N64 emulator
This projects aims to use reinforcement learning algorithms to play the game 2048.
Adversarial attacks on Deep Reinforcement Learning (RL)