Effect of DisCSP variable-ordering heuristics in scale-free networks

Tenda Okimoto, Atsushi Iwasaki, Makoto Yokoo

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 被引用数 (Scopus)


A Distributed Constraint Satisfaction Problem (DisCSP) is a constraint satisfaction problem in which variables and constraints are distributed among multiple agents. Various algorithms for solving DisC-SPs have been developed, which are intended for general purposes, i.e., they can be applied to any network structure. However, if a network has some particular structure, e.g., the network structure is scale-free, we can expect that some specialized algorithms or heuristics, which are tuned for the network structure, can outperform general purpose algorithms/heuristics. In this paper, as an initial step toward developing specialized algorithms for particular network structures, we examine variable-ordering heuristics in scale-free networks. We use the classic asynchronous backtracking algorithm as a baseline algorithm and examine the effect of variable-ordering heuristics. First, we show that the choice of variable-ordering heuristics is more influential in scale-free networks than in random networks. Furthermore, we develop a novel variable-ordering heuristic that is specialized to scale-free networks. Experimental results illustrate that our new variable-ordering heuristic is more effective than a standard degree-based variable-ordering heuristic. Our proposed heuristic reduces the required cycles by 30% at the critical point.

ホスト出版物のタイトルPrinciples and Practice of Multi-Agent Systems - 13th International Conference, PRIMA 2010, Revised Selected Papers
出版ステータス出版済み - 12 1 2012
イベント13th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2010 - Kolkata, インド
継続期間: 11 12 201011 15 2010


名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7057 LNAI


その他13th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2010

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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