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Title: Reinforcement Learning in Python - Valentyn Sichkar

Open Graph Title: Reinforcement Learning in Python

Description: Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

Open Graph Description: Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa

Opengraph URL: https://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python/

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direct link

Domain: sichkar-valentyn.github.io


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Links:

View on GitHubhttps://github.com/sichkar-valentyn/Reinforcement_Learning_in_Python
by Valentyn Sichkarhttps://sichkar-valentyn.github.io
Academia.eduhttps://ifmo.academia.edu/ValentynSichkar
YouTubehttps://www.youtube.com/channel/UCHlzRR0y54SLbcHwLzrUcfw
https://doi.org/10.5281/zenodo.1317898
10.18721/JCSTCS.11206https://doi.org/10.18721/JCSTCS.11206
ResearchGate.net/profile/Valentyn_Sichkarhttps://www.researchgate.net/profile/Valentyn_Sichkar
Matlab implementation of Neural Networkshttps://github.com/sichkar-valentyn/Matlab_implementation_of_Neural_Networks
Knowledge Base Represented by Semantic Web Languagehttps://github.com/sichkar-valentyn/Knowledge_Base_Represented_by_Semantic_Web_Language
Neural Networks for Computer Visionhttps://github.com/sichkar-valentyn/Neural_Networks_for_Computer_Vision
RL_Q-Learning_E-1https://github.com/sichkar-valentyn/Reinforcement_Learning_in_Python/tree/master/RL_Q-Learning_E1
RL_Q-Learning_E-2https://github.com/sichkar-valentyn/Reinforcement_Learning_in_Python/tree/master/RL_Q-Learning_E2
RL_Q-Learning_E-3https://github.com/sichkar-valentyn/Reinforcement_Learning_in_Python/tree/master/RL_Q-Learning_E3
RL_Sarsa_E-1https://github.com/sichkar-valentyn/Reinforcement_Learning_in_Python/tree/master/RL_Sarsa_E1
RL_Sarsa_E-2https://github.com/sichkar-valentyn/Reinforcement_Learning_in_Python/tree/master/RL_Sarsa_E2
RL Q-Learning Environment-1. Experimental resultshttps://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#RL Q-Learning Environment-1. Experimental results
Q-learning algorithm resulted chart for the environment-1https://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#Q-learning algorithm resulted chart for the environment-1
Final Q-table with values from the final shortest route for environment-1https://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#Final Q-table with values from the final shortest route for environment-1
RL Q-Learning Environment-2. Experimental resultshttps://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#RL Q-Learning Environment-2. Experimental results
Q-learning algorithm resulted chart for the environment-2https://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#Q-learning algorithm resulted chart for the environment-2
Final Q-table with values from the final shortest route for environment-1https://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#Final Q-table with values from the final shortest route for environment-1
RL Q-Learning Environment-3. Experimental resultshttps://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#RL Q-Learning Environment-3. Experimental results
Comparison analysis of Q-Learning and Sarsa algorithmshttps://sichkar-valentyn.github.io/Reinforcement_Learning_in_Python#Comparison analysis of Q-Learning and Sarsa algorithms
Valentyn Sichkarhttps://github.com/sichkar-valentyn

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