NDLI: Development of a real-time learning scheduler using reinforcement learning concepts

Content Provider	IEEE Xplore Digital Library
Author	Rabelo, L.C. Jones, A. Yih, Y.
Copyright Year	1994
Description	Author affiliation: Dept. of Ind. & Syst. Eng., Ohio Univ., Athens, OH, USA (Rabelo, L.C.)
Abstract	A scheme for the scheduling of flexible manufacturing systems (FMS) has been developed which divides the scheduling function (built upon a generic controller architecture) into four different steps: candidate rule selection, transient phenomena analysis, multicriteria compromise analysis, and learning. This scheme is based on a hybrid architecture which utilizes neural networks, simulation, genetic algorithms, and induction mechanism. This paper investigates the candidate rule selection process, which selects a small list of scheduling rules from a larger list of such rules. This candidate rule selector is developed by using the integration of dynamic programming and neural networks. The system achieves real-time learning using this approach. In addition, since an expert scheduler is not available, it utilizes reinforcement signals from the environment (a measure of how desirable the achieved state is as measured by the resulting performance criteria). The approach is discussed and further research issues are presented.
Starting Page	291
Ending Page	296
File Size	647310
Page Count	6
File Format	PDF
ISBN	0780319907
ISSN	21589860
DOI	10.1109/ISIC.1994.367802
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-08-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning Job shop scheduling Flexible manufacturing systems Monitoring Neural networks Control systems Transient analysis Genetic algorithms Dynamic programming Constraint optimization
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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