Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
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Updated
Mar 31, 2024 - Python
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
I utilized the A3C (Asynchronous Advantage Actor-Critic) algorithm to train a Deep Q-Learning (DQN) model, specifically tailored to solve the Kungfu gym environment.
PyTorch implementation of A3C (Asynchronous Advantage Actor Critic)
A3C LSTM Atari with Pytorch plus A3G design
Simple A3C implementation with pytorch + multiprocessing
The Asynchronous Advantage Actor Critic (A3C) algorithm is one of the newest algorithms to be developed under the field of Deep Reinforcement Learning Algorithms. This algorithm was developed by Google’s DeepMind which is the Artificial Intelligence division of Google. In this repository, I have my implementations of A3C on Cartpole game, Robot …
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
Play Atari(Breakout) Game by DRL - DQN, Noisy DQN and A3C
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
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
StarCraft II / PySC2 reinforcement learning research
Deep reinforcement learning agent
Deep reinforcement learning using an asynchronous advantage actor-critic (A3C) model.
Attentional Mechanism incorporated in Asynchronous Advantage Actor Critic a3c/a2c deep mind
Simple Reinforcement Learning Framework
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