Iterative broadening

Authors:
Matthew L. Ginsberg;William D. Harvey
Affiliations:
Computer Science Department, Stanford University, Stanford, California;Computer Science Department, Stanford University, Stanford, California
Venue:
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Year:
1990

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Abstract

Conventional blind search techniques generally assume that the goal nodes for a given problem are distributed randomly along the fringe of the search tree. We argue that this is often invalid in practice, suggest that a more reasonable assumption is that decisions made at each point in the search carry equal weight, and show that a new search technique that we call iterative broadening leads to orders-of-magnitude savings in the time needed to search a space satisfying this assumption. Both theoretical and experimental results are presented.