Domain-dependent and domain-independent problem solving techniques

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Heuristic search is a general problem-solving method. Some heuristic search algorithms, like the well-known A algorithm, are domain-independent, in the sense that their knowledge of the problem at-hand is limited to the (1) initial state, (2) state transition operators and their costs, (3) goal-test function, and (4) black-box heuristic function that estimates the value of a state. Prominent examples are A and Weighted A. Other heuristic search algorithms are domain-dependent, that is, customized to solve problems from a specific domain. A well-known example is conflict-directed A, which is specifically designed to solve model-based diagnosis problems. In this paper, we review our recent advancements in both domain-independent and domain-dependent heuristic search, and outline several challenging open questions.

Original languageEnglish
Title of host publicationProceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019
EditorsSarit Kraus
PublisherInternational Joint Conferences on Artificial Intelligence
Pages6411-6415
Number of pages5
ISBN (Electronic)9780999241141
DOIs
StatePublished - 1 Jan 2019
Event28th International Joint Conference on Artificial Intelligence, IJCAI 2019 - Macao, China
Duration: 10 Aug 201916 Aug 2019

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
Volume2019-August
ISSN (Print)1045-0823

Conference

Conference28th International Joint Conference on Artificial Intelligence, IJCAI 2019
Country/TerritoryChina
CityMacao
Period10/08/1916/08/19

ASJC Scopus subject areas

  • Artificial Intelligence

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