The distributed constraint satisfaction problem: Formalization and algorithms

Makoto Yokoo*, Edmund H. Durfee, Toru Ishida, Kazuhiro Kuwabara

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

504 Citations (Scopus)


In this paper, we develop a formalism called a distributed constraint satisfaction problem (distributed CSP) and algorithms for solving distributed CSPs. A distributed CSP is a constraint satisfaction problem in which variables and constraints are distributed among multiple agents. Various application problems in Distributed Artificial Intelligence can be formalized as distributed CSPs. We present our newly developed technique called asynchronous backtracking that allows agents to act asynchronously and concurrently without any global control, while guaranteeing the completeness of the algorithm. Furthermore, we describe how the asynchronous backtracking algorithm can be modified into a more efficient algorithm called an asynchronous weak-commitment search, which can revise a bad decision without exhaustive search by changing the priority order of agents dynamically. The experimental results on various example problems show that the asynchronous weak-commitment search algorithm is, by far more, efficient than the asynchronous backtracking algorithm and can solve fairly large-scale problems.

Original languageEnglish
Pages (from-to)673-685
Number of pages13
JournalIEEE Transactions on Knowledge and Data Engineering
Issue number5
Publication statusPublished - 1998
Externally publishedYes


  • Backtracking algorithms
  • Constraint satisfaction problem
  • Distributed artificial intelligence
  • Iterative improvement algorithm
  • Multiagent systems

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics


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