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Optimal strategies in measurable learning systems on metric spaces

Published online by Cambridge University Press:  14 July 2016

Ernst–Erich Doberkat
Ernst–Erich Doberkat*
Affiliation:
Pädagogische Hochschule Rheinland, Bonn
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Abstract

A dynamic programming approach for the investigation of learning systems is taken. Making use of one-stage decision models and dynamic programs, respectively, two learning models are formulated and the existence of optimal strategies for learning in the respective models is proven.

Keywords

STOCHASTIC MODELS FOR LEARNINGAPPLICATIONS OF ONE-STAGE DECISION MODELSAPPLICATIONS OF DYNAMIC PROGRAMSSET-VALUED MAPPINGS
Type
Research Papers
Information
Journal of Applied Probability , Volume 14 , Issue 4 , December 1977 , pp. 795 - 805
Copyright
Copyright © Applied Probability Trust 1977 

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