Using Swarm-GAP for Distributed Task Allocation in Complex Scenarios

  • Authors:

  • Paulo R. Ferreira, Jr.;Felipe S. Boffo;Ana L. Bazzan

  • Affiliations:

  • Instituto de Informática, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil CEP 91501-970 and Instituto de Ciências Exatas e Tecnológicas, Centro Universitário Fe ...;Instituto de Informática, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil CEP 91501-970;Instituto de Informática, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil CEP 91501-970

  • Venue:
  • Massively Multi-Agent Technology
  • Year:
  • 2008

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Abstract

This paper addresses distributed task allocation in complex scenarios modeled using the distributed constraint optimization problem (DCOP) formalism. It is well known that DCOP, when used to model complex scenarios, generates problems with exponentially growing number of parameters. However, those scenarios are becoming ubiquitous in real-world applications. Therefore, approximate solutions are necessary. We propose and evaluate an algorithm for distributed task allocation. This algorithm, called Swarm-GAP, is based on theoretical models of division of labor in social insect colonies. It uses a probabilistic decision model. Swarm-GAP is experimented both in a scenario from RoboCup Rescue and an abstract simulation environment. We show that Swarm-GAP achieves similar results as other recent proposed algorithm with a reduction in communication and computation. Thus, our approach is highly scalable regarding both the number of agents and tasks.