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.
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Updated
Mar 25, 2019 - Python
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.
EATED 2018 DQN을 이용한 고전게임 강화학습
Beer Game implemented as an OpenAI gym environment.
Custom environment for OpenAI gym
RL Agent for Atari Game Pong
OpenAI Gym environment for the classic Nintendo game Duck Hunt.
Developed a Deep Q Network (DQN) for the cartpole balancing problem (a Google gym environment) using screen (pixel) input to allow generalization to other discrete binary problems and expandability into robotics.
Deep convolutional Q-Learning project powered by Gym
Gym environments for playing soccer
Deep Reinforcement Learning agent playing Space Invaders
OpenAI's PPO baseline applied to the classic game of Snake
A custom implementation of DeepMind's "the commons game"
中国象棋gym环境
Small minimum size gym environments for testing (and maybe finding edge cases)
This fork adds multi-agent social dilemma environments in Gym: CoinGame, (Iterated) Prisonner Dilemma, Stag Hunt, Chicken, Matching Pennies. Gym: A toolkit for developing and comparing reinforcement learning algorithms.
Create new gridworld gym environments easily
Tutorial about implementing custom environments using OpenAI gym framework designed for Software for Intelligent Systems and Artificial Intelligence course.
Repository of implementation of few algorithms for Underactuated Systems in Robotics and solutions to some interesting problems
Documentation and ressources of Kraby, an open-source hexapod robot
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