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Recursive learning method for knowledge-based planning system

โœ Scribed by Yoshitomo Ikkai; Takenao Ohkawa; Norihisa Komoda


Publisher
Springer US
Year
1996
Tongue
English
Weight
470 KB
Volume
7
Category
Article
ISSN
0956-5515

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โœฆ Synopsis


In the status selection planning system, which is a kind of knowledge-based planning system, the quality of the solution depends on the status selection rules. However, it is usually difficult to acquire useful knowledge from human experts. The learning method of a status selection rule using inductive learning is proposed. The status selection rules are divided into several stages according to the planning process. Gathering a training set and learning a part of the knowledge inductively are repeated one by one from the previous stage rules. From the result of application to a job-shop problem, the effectiveness of the proposed method is shown.


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