In this paper we focus on solving DCOPs in computationally demanding scenarios. GDL optimally solves DCOPs, but requires exponentially large cost functions, being impractical in such settings. Function filtering is a technique that reduces the size of cost functions. We improve the effectiveness of function filtering to reduce the amount of resources required to optimally solve DCOPs. As a result, we enlarge the range of problems solvable by algorithms employing function filtering.
Links:
[1] http://www.iiia.csic.es/en/individual/marc-pujol-gonzalez
[2] http://www.iiia.csic.es/en/individual/jesus-cerquides
[3] http://www.iiia.csic.es/en/individual/pedro-meseguer
[4] http://www.iiia.csic.es/en/individual/juan-a-rodriguez-aguilar
[5] http://www.iiia.csic.es/en/publications/export/tagged/4297
[6] http://www.iiia.csic.es/en/publications/export/xml/4297
[7] http://www.iiia.csic.es/en/publications/export/bib/4297
[8] http://www.iiia.csic.es/en/project/at
[9] http://www.iiia.csic.es/en/project/eve
[10] http://www.iiia.csic.es/en/project/recedit