Show all publications

Hybrid Aco/ea Algorithms Applied to the Multi-Agent Patrolling Problem

Download PDFDownload Bibliography in Open DocumentDownload Bibliography in HTMLDownload BibTeXDownload RISDownload Bibliographical Ontology (RDF)
Authors:
Details:
In Proc. of IEEE World Congress on Computational Intelligence (WCCI), 2014.
Abstract:
Patrolling an environment consists in visiting as frequently as possible its most relevant areas in order to supervise, control or protect it. This task is commonly performed by a team of agents that need to coordinate their actions for achieving optimal performance. We address here the problem of multi-agent patrolling in known environments where agents may move at different speeds and visit priorities on some areas may be specified. Two classes of patrolling strategies are studied: the single-cycle strategies and the partition- based strategies. Several single-core and multi-core variants of a template state-of-the-art hybrid algorithm are proposed for generating partition-based strategies. These are experimentally compared with a state-of- the-art heuristic-based algorithm generating single-cycle strategies. Experimental results show that: the heuristic- based algorithm only generates efficient strategies when agents move at the same speeds and no visit priorities have been defined; all single- core variants are equivalent; multi-core hybrid algorithms may improve overall quality or reduce variance of the solutions obtained by single-core algorithms.
Keywords:
Multi-agent patrolling problem ACO evolutionary algorithm multi-core
Publication Category:
International conference with proceedings
Copyright 2010-2019 © Laboratoire Connaissance et Intelligence Artificielle Distribu√©es - Université Bourgogne Franche-Comté - Privacy policy