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# Reinforcement Learning in Python
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Implementing Reinforcement Learning (RL) Algorithms for global path planning in tasks of mobile robot navigation. Comparison analysis of Q-learning and Sarsa algorithms fo the environment with cliff, mouse and cheese.
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<br/>![DOI](https://zenodo.org/badge/131179151.svg)
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<br/>[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1317898.svg)](https://doi.org/10.5281/zenodo.1317898)
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### Reference to:
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Valentyn N Sichkar. Reinforcement Learning Algorithms for global path planning // GitHub platform. DOI: 10.5281/zenodo.1317899
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Valentyn N Sichkar. Reinforcement Learning Algorithms for global path planning // GitHub platform. DOI: 10.5281/zenodo.1317898
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## Description
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RL Algorithms implemented in Python for the task of global path planning for mobile robot. Such system is said to have feedback. The agent acts on the environment, and the environment acts on the agent. At each step the agent:
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### Copyright (c) 2018 Valentyn N Sichkar
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### github.com/sichkar-valentyn
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### Reference to:
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Valentyn N Sichkar. Reinforcement Learning Algorithms for global path planning // GitHub platform. DOI: 10.5281/zenodo.1317899
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Valentyn N Sichkar. Reinforcement Learning Algorithms for global path planning // GitHub platform. DOI: 10.5281/zenodo.1317898

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