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Multi-variable distributed backtracking with sessions

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Abstract

The Constraint Satisfaction Problem (CSP) formalism is used to represent many combinatorial decision problems instances simply and efficiently. However, many such problems cannot be solved on a single, centralized computer for various reasons (e.g., their excessive size or privacy). The Distributed CSP (DisCSP) extends the CSP model to allow such combinatorial decision problems to be modelled and handled. In this paper, we propose a complete DisCSP-solving algorithm, called Distributed Backtracking with Sessions (DBS), which can solve DisCSP so that each agent encapsulates a whole “complex” problem with many variables and constraints. We prove that the algorithm is sound and complete, and generates promising experimental results.

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Notes

  1. 1 The acquaintances are also called neighbors in constraint graphs.

  2. 2 Local solver means here a mechanism (like constraint propagator) to find a solution for the local CSP.

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Acknowledgments

This research was partially financed by the French Ministry of National Education, Research and Technology, The Nord/Pas-de-Calais Region, the French National Center of Scientific Research (CNRS) and the International Campus on Safety and Intermodality in Transportation.

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  1. Univ. de Valenciennes (UVHC) LAMIH UMR CNRS 8201, F-59313, Valenciennes, France

    René Mandiau, Julien Vion, Sylvain Piechowiak & Pierre Monier

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  1. René Mandiau
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Mandiau, R., Vion, J., Piechowiak, S. et al. Multi-variable distributed backtracking with sessions. Appl Intell 41, 736–758 (2014). https://doi.org/10.1007/s10489-014-0532-2

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