collection of examples
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Updated
Dec 9, 2020 - Jupyter Notebook
collection of examples
This notebook trains an agent to navigate a maze and reach a desired destination. It uses the Gym-MiniGrid's fourRoom-v0 environment as the maze. The agent is trained by using reiforcement learning's vanilla policy gradient (REINFORCE) algorithm.
Notebooks covering temporal difference methods using OpenAI Gym
Reinforcement learning class notebooks at HAW Hamburgo university
This repository contains a Jupyter Notebook with an implemenation of a Q-Learning Agent, which learns to solve the n-Chain OpenAI Gym environment
Notebooks and exercises for the Fast Deep Reinforcement Learning Course https://courses.dibya.online/p/fastdeeprl
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