Decomposed utility functions and graphical models for reasoning about preferences

Ronen I. Brafman, Yagil Engel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Recently, Brafman and Engel (2009) proposed new concepts of marginal and conditional utility that obey additive analogues of the chain rule and Bayes rule, which they employed to obtain a directed graphical model of utility functions that resembles Bayes nets. In this paper we carry this analogy a step farther by showing that the notion of utility independence, built on conditional utility, satisfies identical properties to those of probabilistic independence. This allows us to formalize the construction of graphical models for utility functions, directed and undirected, and place them on the firm foundations of Pearl and Paz's axioms of semi-graphoids. With this strong equivalence in place, we show how algorithms used for probabilistic reasoning such as Belief Propagation (Pearl 1988) can be replicated to reasoning about utilities with the same formal guarantees, and open the way to the adaptation of additional algorithms.

Original languageEnglish
Title of host publicationAAAI-10 / IAAI-10 - Proceedings of the 24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference
PublisherAI Access Foundation
Pages267-272
Number of pages6
ISBN (Print)9781577354642
StatePublished - 1 Jan 2010
Event24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10 - Atlanta, GA, United States
Duration: 11 Jul 201015 Jul 2010

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume1

Conference

Conference24th AAAI Conference on Artificial Intelligence and the 22nd Innovative Applications of Artificial Intelligence Conference, AAAI-10 / IAAI-10
Country/TerritoryUnited States
CityAtlanta, GA
Period11/07/1015/07/10

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