Deep Q-Learning of Unity's Banana environment
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Updated
Dec 24, 2018 - Python
Deep Q-Learning of Unity's Banana environment
Deep Q-Network implementation using PyTorch to solve a 2D navigation + rewards collection task.
Python library for TransdecEnvironment Unity model
This project uses Deep Q Network(DQN) to train an agent to navigate a large, square world to collect yellow bananas and avoid blue bananas.
CREATE AN ARTIFICIAL AGENT THAT TAKES USE OF OBSERVATIONAL CLONING TO MIMIC THE TEACHERS ACTIONS BASED ON REINFORCEMENT LEARNING
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AI agent learning to play pong using policy descent, actor critic and other approaches
Tools for generating multiple configs from a single one and scheduling training runs for all configs in the folder
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Solve reacher (unity ml-agents) using deep deterministic policy gradients (DDPG)
Navigation Project - Udacity Deep Reinforcement Learning Nanodegree
Gaussian process optimization using GPyOpt for Unity ML-Agents Toolkit
AINE-DRL is a deep reinforcement learning (DRL) baseline framework. AINE means "Agent IN Environment".
📽 Python package to live stream ML-Agents training process from Google Colab to Twitch/YouTube server.
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