Handling Over-Constrained Problems in Distributed Multi-agent Systems

  • Lingzhong Zhou
  • Abdul Sattar
  • Scott Goodwin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3501)


The distributed constraint satisfaction problem is a general framework used to represent problems in distributed multi-agent systems. In this paper, we describe a detailed investigation of handling over-constrained satisfaction problems in a dynamic and multi-agent environment. We introduce a new algorithm, Over-constrained Dynamic Agent Ordering, that treats under and over-constrained problems uniformly. While the existing approaches generally only consider a single variable per agent, the proposed algorithm can handle multiple variables per agent. In this approach, we use the degree of unsatisfiability as a measure for relaxing constraints, and hence as a way to guide the search towards the best possible solution(s). Through an experimental study, we demonstrate that our algorithm performs better than the one based on asynchronous weak commitment search.


Multiagent System Constraint Satisfaction Problem Constraint Density Neighbouring Agent Constraint Relaxation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Lingzhong Zhou
    • 1
  • Abdul Sattar
    • 1
  • Scott Goodwin
    • 2
  1. 1.Institute for Integrated and Intelligent SystemsGriffith UniversityBrisbaneAustralia
  2. 2.School of Computer ScienceUniversity of WindsorCanada

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