Partially ordered preferences in decision trees: computing strategies with imprecision in probabilities

Daniel Kikuti, Fabio Gagliardi Cozman, Cassio P. de Campos

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

Partially ordered preferences generally lead to choices that do not abide by standard expected utility guidelines; often such preferences are revealed by imprecision in probability values. We investigate five criteria for strategy selection in decision trees with imprecision in probabilities: “extensive” Γ-maximin and Γ-maximax, interval dominance, maximality and E-admissibility. We present algorithms that generate strategies for all these criteria; our main contribution is an algorithm for Eadmissibility that runs over admissible strategies rather than over sets of probability distributions.
Original languageEnglish
Title of host publicationProceedings of the IJCAI Workshop about Advances on Preference Handling
PublisherInternational Joint Conference on Artificial Intelligence (IJCAI)
Pages118-123
Number of pages6
Publication statusPublished - 2005
Externally publishedYes
EventIJCAI-05 Multidisciplinary Workshop on Advances in Preference Handling - Edinburgh, United Kingdom
Duration: 31 Jul 20051 Aug 2005

Workshop

WorkshopIJCAI-05 Multidisciplinary Workshop on Advances in Preference Handling
CountryUnited Kingdom
CityEdinburgh
Period31/07/051/08/05

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    Kikuti, D., Cozman, F. G., & de Campos, C. P. (2005). Partially ordered preferences in decision trees: computing strategies with imprecision in probabilities. In Proceedings of the IJCAI Workshop about Advances on Preference Handling (pp. 118-123). International Joint Conference on Artificial Intelligence (IJCAI).