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Some Notes on Maximum Entropy Utility

The maximum entropy principle is effective in solving decision problems, especially when it is not possible to obtain sufficient information to induce a decision. Among others, the concept of maximum entropy is successfully used to obtain the maximum entropy utility which assigns cardinal utilities...

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Detalles Bibliográficos
Autores principales: Kim, Eun Young, Ahn, Byeong Seok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515130/
https://www.ncbi.nlm.nih.gov/pubmed/33267351
http://dx.doi.org/10.3390/e21070637
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author Kim, Eun Young
Ahn, Byeong Seok
author_facet Kim, Eun Young
Ahn, Byeong Seok
author_sort Kim, Eun Young
collection PubMed
description The maximum entropy principle is effective in solving decision problems, especially when it is not possible to obtain sufficient information to induce a decision. Among others, the concept of maximum entropy is successfully used to obtain the maximum entropy utility which assigns cardinal utilities to ordered prospects (consequences). In some cases, however, the maximum entropy principle fails to produce a satisfactory result representing a set of partial preferences properly. Such a case occurs when incorporating ordered utility increments or uncertain probability to the well-known maximum entropy formulation. To overcome such a shortcoming, we propose a distance-based solution, so-called the centralized utility increments which are obtained by minimizing the expected quadratic distance to the set of vertices that varies upon partial preferences. Therefore, the proposed method seeks to determine utility increments that are adjusted to the center of the vertices. Other partial preferences about the prospects and their corresponding centralized utility increments are derived and compared to the maximum entropy utility.
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spelling pubmed-75151302020-11-09 Some Notes on Maximum Entropy Utility Kim, Eun Young Ahn, Byeong Seok Entropy (Basel) Article The maximum entropy principle is effective in solving decision problems, especially when it is not possible to obtain sufficient information to induce a decision. Among others, the concept of maximum entropy is successfully used to obtain the maximum entropy utility which assigns cardinal utilities to ordered prospects (consequences). In some cases, however, the maximum entropy principle fails to produce a satisfactory result representing a set of partial preferences properly. Such a case occurs when incorporating ordered utility increments or uncertain probability to the well-known maximum entropy formulation. To overcome such a shortcoming, we propose a distance-based solution, so-called the centralized utility increments which are obtained by minimizing the expected quadratic distance to the set of vertices that varies upon partial preferences. Therefore, the proposed method seeks to determine utility increments that are adjusted to the center of the vertices. Other partial preferences about the prospects and their corresponding centralized utility increments are derived and compared to the maximum entropy utility. MDPI 2019-06-27 /pmc/articles/PMC7515130/ /pubmed/33267351 http://dx.doi.org/10.3390/e21070637 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Eun Young
Ahn, Byeong Seok
Some Notes on Maximum Entropy Utility
title Some Notes on Maximum Entropy Utility
title_full Some Notes on Maximum Entropy Utility
title_fullStr Some Notes on Maximum Entropy Utility
title_full_unstemmed Some Notes on Maximum Entropy Utility
title_short Some Notes on Maximum Entropy Utility
title_sort some notes on maximum entropy utility
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515130/
https://www.ncbi.nlm.nih.gov/pubmed/33267351
http://dx.doi.org/10.3390/e21070637
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