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Single-agent parallel window searchParallel window search is applied to single-agent problems by having different processes simultaneously perform iterations of Iterative-Deepening-A(asterisk) (IDA-asterisk) on the same problem but with different cost thresholds. This approach is limited by the time to perform the goal iteration. To overcome this disadvantage, the authors consider node ordering. They discuss how global node ordering by minimum h among nodes with equal f = g + h values can reduce the time complexity of serial IDA-asterisk by reducing the time to perform the iterations prior to the goal iteration. Finally, the two ideas of parallel window search and node ordering are combined to eliminate the weaknesses of each approach while retaining the strengths. The resulting approach, called simply parallel window search, can be used to find a near-optimal solution quickly, improve the solution until it is optimal, and then finally guarantee optimality, depending on the amount of time available.
Document ID
19910059395
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Powley, Curt
(California Univ. Los Angeles, CA, United States)
Korf, Richard E.
(California, University Los Angeles, United States)
Date Acquired
August 15, 2013
Publication Date
May 1, 1991
Publication Information
Publication: IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume: 13
ISSN: 0162-8828
Subject Category
Cybernetics
Accession Number
91A44018
Funding Number(s)
CONTRACT_GRANT: JPL-957523
CONTRACT_GRANT: NSF IRI-88-01939
Distribution Limits
Public
Copyright
Other

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