Reinforcement Learning environments based on the 1993 game Doom
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Updated
Feb 13, 2024 - C++
Reinforcement Learning environments based on the 1993 game Doom
ns3-gym - The Playground for Reinforcement Learning in Networking Research
Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotion.
Visually Realistic Underwater Robotics Simulator UNav-Sim
OpenAI GYM environment for 6-DOF Helicopter simulation
Docker-based, gym-like torcs environment with vision.
Dynamic System solver for reinforcement learning environment. It solves ODE with 4^{th} order Runge-Kutta methods.
This repository contains code for simulating coupled motion of rigid ball and fluid in 2D and this is used as an environment in Gym to train a controller to balance the ball in air.
Chess AI bot using the minimax algorithm, building upon gym-chess. Used Stockfish for the Evaluation Function
C++ implementation of the continuous LunarLander environment.
Gym interface for Walbi robot, the Walking Biped
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.
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