OPUS: An Efficient Admissible Algorithm for Unordered Search

OPUS is a branch and bound search algorithm that enables efficient admissible search through spaces for which the order of search operator application is not significant. The algorithm's search efficiency is demonstrated with respect to very large machine learning search spaces. The use of admi...

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Bibliographic Details
Published inThe Journal of artificial intelligence research Vol. 3; pp. 431 - 465
Main Author Webb, G. I.
Format Journal Article
LanguageEnglish
Published San Francisco AI Access Foundation 01.01.1995
Subjects
Algorithms
Artificial intelligence
Cognitive tasks
Machine learning
Search algorithms
Task complexity
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Summary:OPUS is a branch and bound search algorithm that enables efficient admissible search through spaces for which the order of search operator application is not significant. The algorithm's search efficiency is demonstrated with respect to very large machine learning search spaces. The use of admissible search is of potential value to the machine learning community as it means that the exact learning biases to be employed for complex learning tasks can be precisely specified and manipulated. OPUS also has potential for application in other areas of artificial intelligence, notably, truth maintenance.
ISSN:1076-9757
1076-9757
1943-5037
DOI:10.1613/jair.227