🦾 Utilizing a Deep Deterministic Policy Gradient algorithm to train robotic simulations in continuous action space
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Updated
Sep 25, 2022 - Python
🦾 Utilizing a Deep Deterministic Policy Gradient algorithm to train robotic simulations in continuous action space
My pysc2 rl agent
Deep Reinforcement Learning gym.
Implementation of DQN and DDQN algorithms in Pytorch to play Atari game
RLForge: Modular, reusable implementations of Deep-RL algorithms
Collection of policy gradient based RL agents
Game stat acquisition using neural networks
Reinforcement learning agent which finds a path to the goal in a grid world. This exercise was done as a coursework for course C424 at Imperial College London.
Autonomous Aerial Vehicle
Series of Reinforcement Learning: Q-Learning, Sarsa, SarsaLambda, Deep Q Learning(DQN);一些列强化学习算法,玩OpenAI-gym游戏
A tool for developing reinforcement learning algorithms focused in stock prediction
Master Thesis project that provides a training framework for two player games. TicTacToe and Othello have already been implemented.
🐲 Stanford CS234 : Reinforcement Learning
Implementation of various Reinforcement Learning Algorithms
Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
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