One-Switch Utility Independence

This paper discusses multiattribute preference relations compatible with a value/utility function represented by the Choquet integral with respect to a fuzzy measure, and shows that the additivity of the fuzzy measure is equivalent to each of mutual preferential independence, mutual weak difference independence, mutual difference independence, mutual utility independence, and additive independence.

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Generalized Utility Independence and Some Implications

Operations Research ◽

10.1287/opre.23.5.928 ◽

1975 ◽

Vol 23 (5) ◽

pp. 928-940 ◽

Cited By ~ 35

Author(s):

Peter C. Fishburn ◽

Ralph L. Keeney

Keyword(s):

Generalized Utility ◽

Utility Independence

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Utility independence of multiattribute utility theory is equivalent to standard sequence invariance of conjoint measurement

Journal of Mathematical Psychology ◽

10.1016/j.jmp.2011.08.001 ◽

2011 ◽

Vol 55 (6) ◽

pp. 451-456 ◽

Cited By ~ 5

Author(s):

Han Bleichrodt ◽

Jason N. Doctor ◽

Martin Filko ◽

Peter P. Wakker

Keyword(s):

Utility Theory ◽

Conjoint Measurement ◽

Multiattribute Utility ◽

Multiattribute Utility Theory ◽

Standard Sequence ◽

Utility Independence

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CUI Networks: A Graphical Representation for Conditional Utility Independence

Journal of Artificial Intelligence Research ◽

10.1613/jair.2360 ◽

2008 ◽

Vol 31 ◽

pp. 83-112 ◽

Cited By ~ 12

Author(s):

Y. Engel ◽

M. P. Wellman

Keyword(s):

Graphical Representation ◽

Utility Functions ◽

Multiattribute Utility ◽

Preference Modeling ◽

Network Construction ◽

Functional Decomposition ◽

Multiple Attributes ◽

Utility Independence ◽

Conditional Utility ◽

Graph Nodes

We introduce CUI networks, a compact graphical representation of utility functions over multiple attributes. CUI networks model multiattribute utility functions using the well-studied and widely applicable utility independence concept. We show how conditional utility independence leads to an effective functional decomposition that can be exhibited graphically, and how local, compact data at the graph nodes can be used to calculate joint utility. We discuss aspects of elicitation, network construction, and optimization, and contrast our new representation with previous graphical preference modeling.

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