An environment of the board game Go using OpenAI's Gym API
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Updated
May 3, 2022 - Python
An environment of the board game Go using OpenAI's Gym API
Reinforcement Learning Agents Trained in the CARLA Simulator
A large-scale benchmark for co-optimizing the design and control of soft robots, as seen in NeurIPS 2021.
A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
OpenAI Gym environment designed for training RL agents to control the flight of a two-dimensional drone.
Beer Game implemented as an OpenAI gym environment.
Course work of Reinforcement-Learning-CS6700
Code for reproducing results in ICML 2020 paper "PackIt: A Virtual Environment for Geometric Planning"
Implementations of various RL and Deep RL algorithms in TensorFlow, PyTorch and Keras.
OpenAI Gym environment designed for training RL agents to bring CartPole upright and its further balancing.
A graphical interface for reinforcement learning and gym-based environments.
Simple PyTorch implementation of Deep Q-learning Algorithm to play Lunar Lander.
Simple Minimalistic Gridworld Environment for OpenAI Gym (Simple-MiniGrid)
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
OpenAI Gym environment designed for training RL agents to balance double CartPole.
Using Reinforcement Learning to solve Maze Navigation, Acrobot, Mountain Car
This repository contains the Project for Machine Learning (CSC-736), done under the guidance of Dr. Siming Liu, at Missouri State University.
Solution to the Deep RL Bootcamp labs from UC Berkeley
A customised Open-AI gym environment which simulate the puzzle video game Threes
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