2024-09-12-fargier24a.md

title	abstract	openreview	section	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
Generalized Expected Utility as a Universal Decision Rule – A Step Forward	In order to capture a larger range of decision rules, this paper extends the seminal work of [Friedman and Halpern, 1995, Chu and Halpern, 2003, 2004] about Generalized Expected Utility. We introduce the notion of algebraic mass function (and of algebraic Möbius transform) and provide a new algebraic expression for expected utility based on such functions. This utility, that we call "XEU", generalizes Chu and Halpern’s GEU to non-decomposable measures and allows for the representation of several rules that could not be captured up to this point, and noticeably, of the Choquet integral. A representation theorem is provided that shows that only a very weak condition is needed for a rule in order to be representable as a XEU.	OeOZO9rZj3	Papers	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	fargier24a	0	Generalized Expected Utility as a Universal Decision Rule – A Step Forward	1323	1338	1323-1338	1323	false	Fargier, H\'el\`ene and Pomeret-Coquot, Pierre	given family Hélène Fargier given family Pierre Pomeret-Coquot	2024-09-12		Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence	244	inproceedings	date-parts 2024 9 12	https://raw.githubusercontent.com/mlresearch/v244/main/assets/fargier24a/fargier24a.pdf