Abstract
Distributed constraint optimization problems with finite domains can be solved by asynchronous procedures. ADOPT is the reference algorithm for this kind of problems. Several versions of this algorithm have been proposed, one of them is BnB-ADOPT which changes the nature of the original algorithm from best-first to depth-first search. With BnB-ADOPT, we can assure in some cases that the value of a variable will not be used in the optimal solution. Then, this value can be deleted unconditionally. The contribution of this work consists in propagating these unconditionally deleted values using soft arc consistency techniques, in such a way that they can be known by other variables that share cost functions. When we propagate these unconditional deletions we may generate some new deletions that will also be propagated. The global effect is that we search in a smaller space, causing performance improvements. The effect of the propagation is evaluated on several benchmarks.
This work is partially supported by the project TIN2009-13591-C02-02.
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References
Dechter, R.: Constraint Processing. Morgan Kaufmann, San Francisco (2003)
Larrosa, J.: Node and arc consistency in weighted CSP. In: Proc. of AAAI 2002 (2002)
Larrosa, J., Schiex, T.: In the quest of the best form of local consistency for weighted CSP. In: Proc. of IJCAI 2003 (2003)
Meisels, A., Kaplansky, E., Razgon, I., Zivan, R.: Comparing performance of distributed constraint processing algorithms. In: AAMAS Workshop on Distributed Constraint Reasoning, pp. 86–93 (2002)
Meseguer, P., Rossi, F., Schiex, T.: Handbook of Constraint Programming. In: Soft Constraints, ch. 9. Elsevier, Amsterdam (2006)
Modi, P.J., Shen, W.M., Tambe, M., Yokoo, M.: Adopt: asynchronous distributed constraint optimization with quality guarantees. Artificial Intelligence (161), 149–180 (2005)
Silaghi, M., Yokoo, M.: Nogood-based asynchronous distributed optimization (ADOPT-ng). In: Proc. of AAMAS 2006 (2006)
Yeoh, W., Felner, A., Koenig, S.: Bnb-adopt: An asynchronous branch-and-bound DCOP algorithm. In: Proc. of AAMAS 2008, pp. 591–598 (2008)
Yin, Z.: USC dcop repository. Meeting scheduling and sensor net datasets (2008), http://teamcore.usc.edu/dcop
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Gutierrez, P., Meseguer, P. (2011). Connecting BnB-ADOPT with Soft Arc Consistency: Initial Results. In: Larrosa, J., O’Sullivan, B. (eds) Recent Advances in Constraints. CSCLP 2009. Lecture Notes in Computer Science(), vol 6384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19486-3_2
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DOI: https://doi.org/10.1007/978-3-642-19486-3_2
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