Please use this identifier to cite or link to this item:
metadata.dc.type: conferenceObject
Title: A Self-Organized Algorithm for Distributed Task Allocation in Complex Scenarios..
metadata.dc.creator: Bazzan, Ana Lúcia Cetertich
Ferreira Júnior, Paulo Roberto
Boffo, F. S.
Abstract: 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.
Keywords: Distributed task allocation
Multiagent systems
Citation: FERREIRA JÚNIOR, Paulo Roberto ; BOFFO, F. S. ; BAZZAN, Ana Lúcia Cetertich . A Self-Organized algorithm for distributed task allocation in complex scenarios.. In: Workshop on Coordination and Control in Massively Multi-Agent Systems (CCMMS), 2007, Honolulu, Havaii. Proceedings of the Workshp on Coordination and Control in Massively Multi-Agent Systems (CCMMS). p. 19-33.
Issue Date: 2007
Appears in Collections:Ciência da computação: Trabalhos em eventos

Files in This Item:
File Description SizeFormat 
trabalho_evento_04.pdf174,82 kBAdobe PDFThumbnail

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.