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      Direct Use of Neural Networks for Decision Making

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      ScienceOpen Preprints
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      nearal network, decision making, parameters
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            Abstract

            In most cases the output of a neural network produces a predicted value for the relevant output factor or probabilities for different values of the relevant output factor, and a decision is made based on these values.This paper develops a methodology of using neural networks directly for making decisions without preliminary obtaining the predicted value for the relevant output factor (or probabilities fordifferent values of the relevant output factor). The presented methodology is related to reinforcement learning.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            31 July 2020
            Affiliations
            [1 ] Professor at Department of Mathematical Methods in Economics, Belarus State Economic University (Minsk, Belarus)
            Article
            10.14293/S2199-1006.1.SOR-.PPDOPZQ.v1
            ecc26c85-94a9-4e4c-ae33-b8c09b0a0b6a

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            All data generated or analysed during this study are included in this published article (and its supplementary information files).
            Mathematical software,Numerical methods,Machine learning,Neural & Evolutionary computing,Artificial intelligence,Mathematical economics,Mathematical modeling & Computation
            nearal network, decision making, parameters

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