Max/min-sum distributed constraint optimization through value propagation on an alternating DAG

Roie Zivan, Hilla Peled

Research output: Contribution to conferencePaperpeer-review

26 Scopus citations

Abstract

Distributed Constraint Optimization Problems (DCOPs) are NP-hard and therefore the number of studies that consider incomplete algorithms for solving them is growing. Specifically, the Max-sum algorithm has drawn attention in recent years and has been applied to a number of realistic applications. Unfortunately, in many cases Max-sum does not produce high quality solutions. More specifically, when problems include cycles of various sizes in the factor graph upon which Max-sum performs, the algorithm does not converge and the states that it visits are of low quality. In this paper we advance the research on incomplete algorithms for DCOPs by: (1) Proposing a version of the Max-sum algorithm that operates on an alternating directed acyclic graph (Max-sum-AD), which guarantees convergence in linear time. (2) Identifying major weaknesses of Max-sum and Max-sum-AD that cause inconsistent costs/utilities to be propagated and affect the assignment selection. (3) Solving the identified problems by introducing value propagation to Max-sum-AD. Our empirical study reveals a large improvement in the quality of the solutions produced by Max-sum-AD with value propagation (VP), when solving problems which include cycles, compared with the solutions produced by the standard Max-sum algorithm, Bounded Max-sum and Max-sum-AD with no value propagation.

Original languageEnglish
Pages280-287
Number of pages8
StatePublished - 1 Jan 2012
Event11th International Conference on Autonomous Agents and Multiagent Systems 2012: Innovative Applications Track, AAMAS 2012 - Valencia, Spain
Duration: 4 Jun 20128 Jun 2012

Conference

Conference11th International Conference on Autonomous Agents and Multiagent Systems 2012: Innovative Applications Track, AAMAS 2012
Country/TerritorySpain
CityValencia
Period4/06/128/06/12

Keywords

  • DCOP
  • GDL
  • Incomplete Algorithms

ASJC Scopus subject areas

  • Artificial Intelligence

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