Balancing asymmetry in max-sum using split constraint factor graphs

Liel Cohen, Roie Zivan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Max-sum is a version of Belief Propagation, used for solving DCOPs. On tree-structured problems, Max-sum converges to the optimal solution in linear time. When the constraint graph representing the problem includes multiple cycles, Max-sum might not converge and explore low quality solutions. Damping is a method that increases the chances that Max-sum will converge. Damped Max-sum (DMS) was recently found to produce high quality solutions for DCOP when combined with an anytime framework. We propose a novel method for adjusting the level of asymmetry in the factor graph, in order to achieve a balance between exploitation and exploration, when using Max-sum for solving DCOPs. By converting a standard factor graph to an equivalent split constraint factor graph (SCFG), in which each function-node is split to two function-nodes, we can control the level of asymmetry for each constraint. Our empirical results demonstrate that by applying DMS to SCFGs with a minor level of asymmetry we can find high quality solutions in a small number of iterations, even without using an anytime framework. As part of our investigation of this success, we prove that for a factor-graph with a single constraint, if this constraint is split symmetrically, Max-sum applied to the resulting cycle is guaranteed to converge to the optimal solution and demonstrate that for an asymmetric split, convergence is not guaranteed.

Original languageAmerican English
Title of host publicationPrinciples and Practice of Constraint Programming - 24th International Conference, CP 2018, Proceedings
EditorsJohn Hooker
PublisherSpringer Verlag
Number of pages19
ISBN (Print)9783319983332
StatePublished - 1 Jan 2018
Event24th International Conference on the Principles and Practice of Constraint Programming, CP 2018 - Lille, France
Duration: 27 Aug 201831 Aug 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11008 LNCS


Conference24th International Conference on the Principles and Practice of Constraint Programming, CP 2018

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Balancing asymmetry in max-sum using split constraint factor graphs'. Together they form a unique fingerprint.

Cite this