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Constructing a unifying theory of dynamic programming DCOP algorithms via the generalized distributive law

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Abstract

In this paper we propose a novel message-passing algorithm, the so-called Action-GDL, as an extension to the generalized distributive law (GDL) to efficiently solve DCOPs. Action-GDL provides a unifying perspective of several dynamic programming DCOP algorithms that are based on GDL, such as DPOP and DCPOP algorithms. We empirically show how Action-GDL using a novel distributed post-processing heuristic can outperform DCPOP, and by extension DPOP, even when the latter uses the best arrangement provided by multiple state-of-the-art heuristics.

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Authors and Affiliations

  1. IIIA, Artificial Intelligence Research Institute, Spanish National Research Council, Campus UAB, 08193, Bellaterra, Spain

    Meritxell Vinyals & Juan A. Rodriguez-Aguilar

  2. WAI, Departament Matemàtica Aplicada i Anàlisi, Universitat de Barcelona, Gran Via 585, 08191, Barcelona, Spain

    Jesús Cerquides

Authors
  1. Meritxell Vinyals
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  2. Juan A. Rodriguez-Aguilar
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  3. Jesús Cerquides
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Correspondence to Meritxell Vinyals.

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Vinyals, M., Rodriguez-Aguilar, J.A. & Cerquides, J. Constructing a unifying theory of dynamic programming DCOP algorithms via the generalized distributive law. Auton Agent Multi-Agent Syst 22, 439–464 (2011). https://doi.org/10.1007/s10458-010-9132-7

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  • DOI: https://doi.org/10.1007/s10458-010-9132-7

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