Deep Reinforcement Learning DQN on Unity ML Agent
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Updated
Sep 2, 2018 - HTML
Deep Reinforcement Learning DQN on Unity ML Agent
This project explores a deep reinforcement learning technique to train an agent to play atari pong game from OpenAI Gym. OpenAI Gym is a toolkit to develop and compare reinforcement learning algorithms. The learning agent takes raw pixels from the atari emulator and predicts an action that is fed back into the emulator via OpenAI interface. The …
Reinforcement Learning Agents learn with Deep-Q-Learning Network to collect superior and avoid inferior items.
Project developed as part of the Udacity Deep Reinforcement Learning Nanodegree Program
Deep Reinforcement Learning using pytorch - Bananas
Artificial Intelligence Fundamentals Project by Paul Magos and Stefano Zanoni.
Udacity's Deep Reinforcement Learning Nanodegree Project - Navigation
Implementation of Policy Gradient Methods for Continuous and Discrete Action Spaces
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