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Distributed Constraint Programming with Agents

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Adaptive and Intelligent Systems (ICAIS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6943))

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Abstract

Many combinatorial optimization problems lend themselves to be modeled as distributed constraint optimization problems (DisCOP). Problems such as job shop scheduling have an intuitive matching between agents and machines. In distributed constraint problems, agents control variables and are connected via constraints. We have equipped these agents with a full constraint solver. This makes it possible to use global constraint and advanced search schemes.

By empowering the agents with their own solver, we overcome the low performance that often haunts distributed constraint satisfaction problems (DisCSP). By using global constraints, we achieve far greater pruning than traditional DisCSP models. Hence, we dramatically reduce communication between agents.

Our experiments show that both global constraints and advanced search schemes are necessary to optimize job shop schedules using DisCSP.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Lund University, Sweden

    Carl Christian Rolf & Krzysztof Kuchcinski

Authors
  1. Carl Christian Rolf
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  2. Krzysztof Kuchcinski
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Editor information

Editors and Affiliations

  1. Department of Informatics-Systems, University of Klagenfurt, Universitätsstr. 65-67, 9020, Klagenfurt, Austria

    Abdelhamid Bouchachia

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Rolf, C.C., Kuchcinski, K. (2011). Distributed Constraint Programming with Agents. In: Bouchachia, A. (eds) Adaptive and Intelligent Systems. ICAIS 2011. Lecture Notes in Computer Science(), vol 6943. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23857-4_32

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  • DOI: https://doi.org/10.1007/978-3-642-23857-4_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23856-7

  • Online ISBN: 978-3-642-23857-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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