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IDB-ADOPT: A Depth-First Search DCOP Algorithm

  • William Yeoh
  • Ariel Felner
  • Sven Koenig
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5655)

Abstract

Many agent coordination problems can be modeled as distributed constraint optimization (DCOP) problems. ADOPT is an asynchronous and distributed search algorithm that is able to solve DCOP problems optimally. In this paper, we introduce Iterative Decreasing Bound ADOPT (IDB-ADOPT), a modification of ADOPT that changes the search strategy of ADOPT from performing one best-first search to performing a series of depth-first searches. Each depth-first search is provided with a bound, initially a large integer, and returns the first solution whose cost is smaller than or equal to the bound. The bound is then reduced to the cost of this solution minus one and the process repeats. If there is no solution whose cost is smaller than or equal to the bound, it returns a cost-minimal solution. Thus, IDB-ADOPT is an anytime algorithm that solves DCOP problems with integer costs optimally. Our experimental results for graph coloring problems show that IDB-ADOPT runs faster (that is, needs fewer cycles) than ADOPT on large DCOP problems, with savings of up to one order of magnitude.

Keywords

ADOPT DCOP Distributed Constraint Optimization  Distributed Search Algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • William Yeoh
    • 1
  • Ariel Felner
    • 2
  • Sven Koenig
    • 1
  1. 1.Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Information Systems EngineeringBen-Gurion University of the NegevBeer-ShevaIsrael

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