Title :
The Gravitational Strategy for the Timed Patrolling
Author :
Sampaio, Pablo A. ; Ramalho, Geber ; Tedesco, Patrícia
Author_Institution :
Dept. de Estatistica e Inf., Univ. Fed. Rural de Pernambuco (UFRPE), Recife, Brazil
Abstract :
A great number of techniques were already applied to the non-adversarial variation of the multiagent patrolling problem. Experiments suggest that, for general graphs, all those approaches are inferior to a strategy based on the travelling salesman problem (TSP), in which agents are distributed equidistantly along the TSP-cycle. This approach, however, is neither optimal nor scalable. In this article, we present a novel patrolling strategy which tries to overcome these limitations. Inspired on Newton´s law of gravitation, our approach consists in assigning to each node of the graph an abstract mass which grows while the node remains unvisited, creating a force that attracts agents to it. We defined some variations of our approach and experimentally compared them to the TSP-based strategy, concluding that our approach performs better in general.
Keywords :
graph theory; multi-agent systems; travelling salesman problems; TSP-based strategy; general graphs; gravitational strategy; multiagent patrolling problem; nonadversarial variation; timed patrolling; travelling salesman problem; Artificial intelligence; Equations; Force; Mathematical model; Measurement; Robots; Traveling salesman problems; multiagent system; security agents; timed patrolling;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International Conference on
Conference_Location :
Arras
Print_ISBN :
978-1-4244-8817-9
DOI :
10.1109/ICTAI.2010.24