Multi-goal pathfinding in ubiquitous environments: modeling and exploiting knowledge to satisfy goals

O. Kem, Flavien Balbo, Antoine Zimmermann
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Abstract

Multi-goal pathfinding (MGPF) is a problem of searching for a path between a start and a destination allowing a set of goals to be satisfied. We address MGPF in ubiquitous environments that accommodate cyber, physical and social (CPS) entities from smart objects to sensors and to humans. Given a MGPF problem in a pervasive environment, our approach aims at exploiting data from various resources including CPS entities located in the environment and external resources such as the Web to solve the problem. In this paper, we present a knowledge model for describing a ubiquitous environment integrating its spatial dimension, CPS entities it contains and its relevant resources. A global view of the approach is provided. We address particularly one of the challenges in MGPF, namely goal satisfaction problem, which consists of identifying through which entities a goal can be satisfied. Towards this aim, we design an ontology to formally model CPS entities, goals and their relations. We describe a method to exploit modeled knowledge in order to solve the goal satisfaction problem.
泛在环境中的多目标寻径:建模和利用知识来满足目标
多目标寻径(multigoal pathfinding,简称MGPF)是一种从起点到终点之间寻找一条路径的问题,允许满足一组目标。我们在无处不在的环境中解决MGPF问题,这些环境可容纳从智能对象到传感器和人类的网络、物理和社会(CPS)实体。考虑到一个普遍环境中的MGPF问题,我们的方法旨在利用来自各种资源的数据,包括位于环境中的CPS实体和外部资源(如Web)来解决问题。本文提出了一种基于空间维度、CPS实体及其相关资源的泛在环境知识模型。提供了该方法的全局视图。我们特别讨论了MGPF中的一个挑战,即目标满意度问题,该问题包括确定通过哪些实体可以实现目标。为此,我们设计了一个本体,对CPS实体、目标及其关系进行形式化建模。提出了一种利用建模知识解决目标满足问题的方法。
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