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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Main Authors: Eun Young Kim, Byeong Seok Ahn
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/21/7/637
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author Eun Young Kim
Byeong Seok Ahn
author_facet Eun Young Kim
Byeong Seok Ahn
author_sort Eun Young Kim
collection DOAJ
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 doaj.art-755944d63790480b88dbb5bc9123c5dd2022-12-22T04:10:18ZengMDPI AGEntropy1099-43002019-06-0121763710.3390/e21070637e21070637Some Notes on Maximum Entropy UtilityEun Young Kim0Byeong Seok Ahn1Department of Neurosurgery, Gachon University Gil Medical Center, 21 Namdongdaero 774, Namdong, Incheon 21565, KoreaCollege of Business and Economics, Chung-Ang University, 221 Heukseok Dongjak, Seoul 06974, KoreaThe 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.https://www.mdpi.com/1099-4300/21/7/637decision analysisutilitymaximum entropy
spellingShingle Eun Young Kim
Byeong Seok Ahn
Some Notes on Maximum Entropy Utility
Entropy
decision analysis
utility
maximum entropy
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 decision analysis
utility
maximum entropy
url https://www.mdpi.com/1099-4300/21/7/637
work_keys_str_mv AT eunyoungkim somenotesonmaximumentropyutility
AT byeongseokahn somenotesonmaximumentropyutility