ikostrikov/pytorch-a3c
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
This project helps machine learning researchers implement and experiment with the Asynchronous Advantage Actor Critic (A3C) algorithm for reinforcement learning. It takes in environment specifications and training parameters, and outputs a trained agent capable of learning complex tasks like playing games. This is used by researchers focused on developing and evaluating reinforcement learning agents.
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Use this if you are a machine learning researcher specifically interested in implementing and studying the A3C algorithm for deep reinforcement learning problems.
Not ideal if you are looking for the most performant or cutting-edge reinforcement learning algorithm, as A2C, PPO, or ACKTR might offer better results and are recommended by the author.
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Sep 25, 2019
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