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A Fuzzy Path Planning System Based on a Collaborative Reinforcement Learning

Chaymaa Lamini(1*), Youssef Fathi(2), Said Benhlima(3)

(1) Faculty of Science, Moulay Ismail University, Computer Science Department, Morocco
(2) Faculty of Science, Moulay Ismail University, Computer Science Department, Morocco
(3) Faculty of Science, Moulay Ismail University, Computer Science Department, Morocco
(*) Corresponding author


DOI: https://doi.org/10.15866/ireaco.v10i2.10623

Abstract


In this paper, we present a novel collaborative Q-Learning based path planning system using Holonic Multi Agent System architecture, and the Fuzzy Inference System, to be used in autonomous mobile robots, represented as head-holons, in order to find the optimal path among any starting point, and a goal in a to 2D grid environment. The decision of the navigation is provided by a fuzzy system controller and then it is verified by a sensor validator.
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Keywords


Multi-Agent Systems; Reinforcement Learning; Autonomous Robots; Q-Learning; Path Planning; Fuzzy System

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References


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