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Discrete sequence prediction and its applicationsLearning from experience to predict sequences of discrete symbols is a fundamental problem in machine learning with many applications. We apply sequence prediction using a simple and practical sequence-prediction algorithm, called TDAG. The TDAG algorithm is first tested by comparing its performance with some common data compression algorithms. Then it is adapted to the detailed requirements of dynamic program optimization, with excellent results.
Document ID
19920017548
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Laird, Philip
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
September 6, 2013
Publication Date
January 1, 1992
Subject Category
Cybernetics
Report/Patent Number
NASA-TM-107865
FIA-92-01
NAS 1.15:107865
Report Number: NASA-TM-107865
Report Number: FIA-92-01
Report Number: NAS 1.15:107865
Accession Number
92N26791
Funding Number(s)
CONTRACT_GRANT: NSF INT-90-08726
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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