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Automatically Decomposing Configuration Problems Luca Anselma, Diego Magro and Pietro Torasso
 

Summary: Automatically Decomposing Configuration Problems
Luca Anselma, Diego Magro and Pietro Torasso
Dipartimento di Informatica, Universit`a di Torino
Corso Svizzera 185; 10149 Torino; Italy
anselma,magro,torasso @di.unito.it
Abstract. Configuration was one of the first tasks successfully approached via
AI techniques. However, solving configuration problems can be computationally
expensive. In this work, we show that the decomposition of a configuration prob-
lem into a set of simpler and independent subproblems can decrease the com-
putational cost of solving it. In particular, we describe a novel decomposition
technique exploiting the compositional structure of complex objects and we show
experimentally that such a decomposition can improve the efficiency of configu-
rators.
1 Introduction
Each time we are given a set of components and we need to put (a subset of) them
together in order to build an artifact meeting a set of requirements, we actually have to
solve a configuration problem. Configuration problems can concern different domains.
For instance, we might want to configure a PC, given different kinds of CPUs, memory
modules, and so on; or a car, given different kinds of engines, gears, etc. Or we might
also want to configure abstract entities in non-technical domains, such as students' cur-

  

Source: Anselma, Luca - Dipartimento di Informatica, UniversitÓ di Torino

 

Collections: Computer Technologies and Information Sciences