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http://hdl.handle.net/11718/20800
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DC Field | Value | Language |
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dc.contributor.author | Aggarwal, Manish | |
dc.date.accessioned | 2018-06-09T11:47:55Z | |
dc.date.available | 2018-06-09T11:47:55Z | |
dc.date.issued | 2018-04-25 | |
dc.identifier.uri | http://hdl.handle.net/11718/20800 | |
dc.description.abstract | We introduce a novel entropy framework for the computation of utility on the basis of an agent’s subjective evaluation of the granularised information source values. A concept of evaluating agent as an information gain function of this entropy framework is presented, which takes as its arguments both an information source value and the agent’s evaluation of the same. A method to model the agent’s perceived utility values is proposed. Based on these values, several new measures are designed for the evaluation of the information source values, perceived utilities, and the evaluating agent. A real application is included. | en_US |
dc.publisher | Taylor & Francis Group | en_US |
dc.subject | Expected utility | en_US |
dc.subject | fuzzy sets | en_US |
dc.subject | Information sets | en_US |
dc.subject | Shannon transforms | en_US |
dc.subject | Hanman–Anirban entropy function | en_US |
dc.subject | Multi-attribute decision-making | en_US |
dc.title | Modelling subjective utility through entropy | en_US |
dc.type | Article | en_US |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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Modellingsubjective.pdf Restricted Access | 2.11 MB | Adobe PDF | View/Open Request a copy |
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