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Modelling and exploiting knowledge of the environment : A multi-agent approach to multi-goal pathfinding in ubiquitous environment

Abstract : From intelligent artificial personal assistants to smart cities, we are experiencing the shifting towards Internet of Things (IoT), ubiquitous computing, and artificial intelligence. Cyber-physical entities are embedded in social environments of various scales from smart homes, to smart airports, to smart cities, and the list continues.This paradigm shift coupled with ceaseless expansion of the Web supplies us with tremendous amount of useful information and services, which creates opportunities for classical problems to be addressed in new, different, and potentially more efficient manners. Along with the new possibilities, we are, at the same time, presented with new constraints, problems, and challenges. Multi-goal pathfinding, a variant of the classical pathfinding, is a problem of finding a path between a start and a destination which also allows a set of goals to be satisfied along the path. The aim of this dissertation is to propose a solution to solve multi-goal pathfinding in ubiquitous environments such as smart transits. In our solution, to provide an abstraction of the environment, we proposed a knowledge model based on the semantic web technologies to describe a ubiquitous environment integrating its cybernetic, physical, and social dimensions. To perform the search, we developed a multi-agent algorithm based on a collaborative and incremental search algorithm that exploits the knowledge of the environment to find the optimal path. The proposed algorithm continuously adapts the path to take into account the dynamics of the environment.
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Submitted on : Thursday, June 25, 2020 - 11:06:12 AM
Last modification on : Saturday, June 27, 2020 - 3:07:06 AM
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  • HAL Id : tel-02880717, version 1



Oudom Kem. Modelling and exploiting knowledge of the environment : A multi-agent approach to multi-goal pathfinding in ubiquitous environment. Other [cs.OH]. Université de Lyon, 2018. English. ⟨NNT : 2018LYSEM023⟩. ⟨tel-02880717⟩



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