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Title	Trust In Smart City Mobility Applications: A Multi-Agent System Perspective
ID_Doc	59071
Authors	Javaherian M.
Year	2025
Published	U.Porto Journal of Engineering, 11, 1
DOI	http://dx.doi.org/10.24840/2183-6493_0011-001_002665
Abstract	This chapter presents a recommendation system framework for smart mobility applications, emphasizing traffic monitoring and parking management in smart cities. Using Reinforcement Learning (RL) and Social Network (SN) concepts, the methodology classifies agents as trustworthy or untrustworthy, tackling multi-agent system challenges in uncertain environments. The research aims to create algorithms and models for safe, efficient, sustainable mobility solutions, addressing data exchange and decision-making issues. Agents gather and process information, make decisions with incomplete data, and interact to achieve goals. Real-world data will validate the approach, enhancing decision-making and improving urban mobility. © 2025, Universidade do Porto - Faculdade de Engenharia. All rights reserved.
Author Keywords	Multi-agent System; Reinforcement Learning; Smart City; Social Networks; Transportation System; Trustworthiness

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