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Related papers: Recovering utility

200 papers

Motivated by recent developments in designing algorithms based on individual item scores for solving utility maximization problems, we study the framework of using test scores, defined as a statistic of observed individual item performance…

Data Structures and Algorithms · Computer Science 2022-02-28 Dabeen Lee , Milan Vojnovic , Se-Young Yun

Gambles are random variables that model possible changes in monetary wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes.…

Economics · Quantitative Finance 2016-02-03 Ole Peters , Murray Gell-Mann

This paper introduces conceptual relations that synthesize utilitarian and logical concepts, extending the logics of preference of Rescher. We define first, in the context of a possible worlds model, constraint-dependent measures that…

Artificial Intelligence · Computer Science 2013-03-26 Enrique H. Ruspini

The choice of admissible trading strategies in mathematical modelling of financial markets is a delicate issue, going back to Harrison and Kreps (1979). In the context of optimal portfolio selection with expected utility preferences this…

Computational Finance · Quantitative Finance 2017-07-25 Sara Biagini , Aleš Černý

Operation management problems (such as Production Planning and Scheduling) are represented and formulated as optimization models. The resolution of such optimization models leads to solutions which have to be operated in an organization.…

Artificial Intelligence · Computer Science 2015-11-19 Oumaima Khaled

Contextuality has been identified as a potential resource responsible for the quantum advantage in several tasks. It is then necessary to develop a resource-theoretic framework for contextuality, both in its standard and generalized forms.…

Quantum Physics · Physics 2018-06-27 Cristhiano Duarte , Barbara Amaral

Interest has been growing in decision-focused machine learning methods which train models to account for how their predictions are used in downstream optimization problems. Doing so can often improve performance on subsequent decision…

Machine Learning · Computer Science 2025-03-03 Santiago Cortes-Gomez , Carlos Patiño , Yewon Byun , Steven Wu , Eric Horvitz , Bryan Wilder

Under the assumption of (positive) homogeneity (PH in the sequel) of the corresponding utility functions, we construct polynomial time algorithms for the weak separability, the collective consumption behavior and some related problems.…

Data Structures and Algorithms · Computer Science 2018-01-04 Alexander Shananin , Sergey Tarasov

We propose an efficient algorithm for estimation of possibility based qualitative expected utility. It is useful for decision making mechanisms where each possible decision is assigned a multi-attribute possibility distribution. The…

Artificial Intelligence · Computer Science 2012-07-09 Jakub Brzostowski , Ryszard Kowalczyk

In previous work cite{Ha98:Towards} we presented a case-based approach to eliciting and reasoning with preferences. A key issue in this approach is the definition of similarity between user preferences. We introduced the probabilistic…

Artificial Intelligence · Computer Science 2013-01-14 Vu A. Ha , Peter Haddawy , John Miyamoto

In this paper, we first consider a Bayesian framework and model the "utility function" in terms of fuzzy random variables. On the basis of this model, we define the "prior (fuzzy) expected utility" associated with each action, and the…

Artificial Intelligence · Computer Science 2013-04-08 Maria Angeles Gil , Pramod Jain

This paper shows how we can combine logical representations of actions and decision theory in such a manner that seems natural for both. In particular we assume an axiomatization of the domain in terms of situation calculus, using what is…

Artificial Intelligence · Computer Science 2013-02-18 David L. Poole

A differentially private selection algorithm outputs from a finite set the item that approximately maximizes a data-dependent quality function. The most widely adopted mechanisms tackling this task are the pioneering exponential mechanism…

Cryptography and Security · Computer Science 2022-08-05 Gonzalo Munilla Garrido , Florian Matthes

Adaptive decision-making in biological and artificial intelligence requires balancing the exploitation of known outcomes with the exploration of uncertain alternatives. Although prior work suggests that uncertainty generally promotes…

Artificial Intelligence · Computer Science 2026-05-20 Payam Piray

The ideas of aleatoric and epistemic uncertainty are widely used to reason about the probabilistic predictions of machine-learning models. We identify incoherence in existing discussions of these ideas and suggest this stems from the…

Machine Learning · Computer Science 2025-08-19 Freddie Bickford Smith , Jannik Kossen , Eleanor Trollope , Mark van der Wilk , Adam Foster , Tom Rainforth

To answer questions of "causes of effects", the probability of necessity is introduced for assessing whether or not an observed outcome was caused by an earlier treatment. However, the statistical inference for probability of necessity is…

Methodology · Statistics 2025-04-14 Ping Zhang , Ruoyu Wang , Wang Miao

To study the assumption that the utility maximization hypothesis implicitly adds to consumer theory, we consider a mathematical representation of pre-marginal revolution consumer theory based on subjective exchange ratios. We introduce two…

Theoretical Economics · Economics 2025-11-19 Yuhki Hosoya

Ambiguity and ambiguity aversion have been widely studied in decision theory and economics both at a theoretical and an experimental level. After Ellsberg's seminal studies challenging subjective expected utility theory (SEUT), several…

Physics and Society · Physics 2018-03-20 Diederik Aerts , Sandro Sozzo

We provide a general theoretical analysis of expected out-of-sample utility, also referred to as decision-theoretic classification, for non-decomposable binary classification metrics such as F-measure and Jaccard coefficient. Our key result…

Machine Learning · Computer Science 2015-05-08 Nagarajan Natarajan , Oluwasanmi Koyejo , Pradeep Ravikumar , Inderjit S. Dhillon

Richard Cox [1] set the axiomatic foundations of probable inference and the algebra of propositions. He showed that consistency within these axioms requires certain rules for updating belief. In this paper we use the analogy between…

Artificial Intelligence · Computer Science 2007-05-23 Ali E. Abbas