Uncertainty and change

Kenneth N. Brown*, Ian Miguel

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

15 Citations (Scopus)

Abstract

Many real and important problems involve change and uncertainty. Solutions are required that take account of vagueness in the problem description, or that minimise the effect of the uncertainty on the solution. Basic approaches to handling change include rapid reaction through re-specifying the problems and re-solving when the changes occur, preparing to change by maintaining explanations and data structures that will allow the solver to avoid repeating work, or proactively generating solutions that are robust, by explicitly reasoning about the possible changes. A number of different techniques have been developed, and they have demonstrated that constraint programming methods can be extended to handle many different forms of dynamism and uncertainty, and that many exemplar problems can be solved efficiently. Constraint programming toolkits need to be extended with facilities to handle such problems. Further work is required to establish which of the techniques and frameworks are practical candidates, and to integrate this body of research with the many other research fields which deal with change and uncertainty. Finally, for an alternative viewpoint on the material in this chapter, the reader is directed to the survey by Verfaillie and Jussien [72].

Original languageEnglish
Title of host publicationHandbook of constraint programming
EditorsFrancesca Rossi, Peter van Beek, Toby Walsh
Place of PublicationAmsterdam
PublisherElsevier
Chapter21
Pages731-760
Number of pages30
ISBN (Print)9780444527264
DOIs
Publication statusPublished - 2006

Publication series

NameFoundations of artificial intelligence (Elsevier)
Volume2
ISSN (Print)1574-6526

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