A Self-Organized Algorithm for Distributed Task Allocation in Complex Scenarios..

• Autor(a) principal: Bazzan, Ana Lúcia Cetertich
• Data de Publicação: 2007
• Outros Autores: Ferreira Júnior, Paulo Roberto, Boffo, F. S.
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UFPel - Guaiaca
• Texto Completo: http://guaiaca.ufpel.edu.br/handle/123456789/88
• topic: Distributed task allocation; GAP; DCOP; Multiagent systems

This paper addresses distributed task allocation in complex scenarios modeled using the distributed constraint optimization problem (DCOP) formalism. We see a complex scenario in distributed task alloca- tion as the one in which small instances formalized as a DCOP generate large problems with exponentially growing parameters. Such scenarios are becoming more and more ubiquitous in real-world applications. We propose and evaluate a novel self-organized algorithm for distributed task allocation based on theoretical models of division of labor in social insect colonies, called Swarm-GAP. Our algorithm uses a probabilistic decision model, based on the social insects tendency of performing certain tasks. Swarm-GAP was experimented in an abstract centralized simulation en- vironment. We show that Swarm-GAP achieves similar results as other recent proposed algorithm with a dramatic reduction in communication and computation. Thus, our approach is highly scalable regarding both the number of agents and tasks.