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Decision-making problems often feature uncertainty stemming from heterogeneous and context-dependent human preferences. To address this, we propose a sequential learning-and-optimization pipeline to learn preference distributions and…

Machine Learning · Computer Science 2026-03-19 Benjamin Hudson , Laurent Charlin , Emma Frejinger

The aim of this paper is to propose a many-valued modal framework to formalize reasoning with both graded preferences and propositions, in the style of van Benthem et al.'s classical modal logics for preferences. To do so, we start from Bou…

Logic in Computer Science · Computer Science 2019-11-18 Amanda Vidal , Francesc Esteva , Lluis Godo

Machine learning (ML) applications have automated numerous real-life tasks, improving both private and public life. However, the black-box nature of many state-of-the-art models poses the challenge of model verification; how can one be sure…

Machine Learning · Computer Science 2022-01-19 Ioannis Papantonis , Vaishak Belle

We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence,…

Econometrics · Economics 2021-02-11 Levon Barseghyan , Maura Coughlin , Francesca Molinari , Joshua C. Teitelbaum

We introduce an Attention Overload Model that captures the idea that alternatives compete for the decision maker's attention, and hence the attention that each alternative receives decreases as the choice problem becomes larger. Using this…

Theoretical Economics · Economics 2024-09-17 Matias D. Cattaneo , Paul Cheung , Xinwei Ma , Yusufcan Masatlioglu

We develop a theory of quantum rational decision making in the tradition of Anscombe and Aumann's axiomatisation of preferences on horse lotteries. It is essentially the Bayesian decision theory generalised to the space of Hermitian…

Quantum Physics · Physics 2016-12-08 Alessio Benavoli , Alessandro Facchini , Marco Zaffalon

An important characteristic of many logics for Artificial Intelligence is their nonmonotonicity. This means that adding a formula to the premises can invalidate some of the consequences. There may, however, exist formulae that can always be…

Artificial Intelligence · Computer Science 2007-05-23 J. Engelfriet

We consider the problem of learning the preferences of a heterogeneous population by observing choices from an assortment of products, ads, or other offerings. Our observation model takes a form common in assortment planning applications:…

Machine Learning · Statistics 2016-06-09 Nathan Kallus , Madeleine Udell

The weak axiom of revealed preference (WARP) ensures that the revealed preference (i) is a preference relation (i.e., it is complete and transitive) and (ii) rationalizes the choices. However, when WARP fails, either one of these two…

Theoretical Economics · Economics 2024-01-15 Pablo Schenone

The paper introduces a generalization for known probabilistic models such as log-linear and graphical models, called here multiplicative models. These models, that express probabilities via product of parameters are shown to capture…

Artificial Intelligence · Computer Science 2012-06-18 Ydo Wexler , Christopher Meek

We propose a method for variable selection in discriminant analysis with mixed categorical and continuous variables. This method is based on a criterion that permits to reduce the variable selection problem to a problem of estimating…

Statistics Theory · Mathematics 2017-03-14 Alban Mbina Mbina , Guy Martial Nkiet , Fulgence Eyi Obiang

Preferences play a key role in determining what goals/constraints to satisfy when not all constraints can be satisfied simultaneously. In this work, we study preference-based planning in a stochastic system modeled as a Markov decision…

Formal Languages and Automata Theory · Computer Science 2022-03-28 Abhishek Ninad Kulkarni , Jie Fu

We present a modal logic based approach to the so-called endophysical quantum universe. In particular, we treat the problem of preferred bases and that of state reduction by employing an eclectic collection of methods including Baltag's…

Quantum Physics · Physics 2007-05-23 A. M. Lisewski

We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main…

Multiagent Systems · Computer Science 2020-11-06 Kshitij Kulkarni , Sven Neth

The war of attrition with two-sided asymmetric information is a foundational model in political economy, yet it generically admits a continuum of perfect Bayesian equilibria. This paper characterizes the sources of equilibrium multiplicity.…

Theoretical Economics · Economics 2026-03-17 Martin Castillo-Quintana , Gianfranco Miranda-Romero

We consider the problem of automatically proving resource bounds. That is, we study how to prove that an integer-valued resource variable is bounded by a given program expression. Automatic resource-bound analysis has recently received…

Programming Languages · Computer Science 2021-10-15 Tianhan Lu , Bor-Yuh Evan Chang , Ashutosh Trivedi

Individual choices often depend on the order in which the decisions are made. In this paper, we expose a general theory of measurable systems (an example of which is an individual's preferences) allowing for incompatible (non-commuting)…

Physics and Society · Physics 2007-06-20 V. I. Danilov , A. Lambert-Mogiliansky

Complexity of the problem of choosing among uncertain acts is a salient feature of many of the environments in which departures from expected utility theory are observed. I propose and axiomatize a model of choice under uncertainty in which…

Theoretical Economics · Economics 2022-10-17 Quitzé Valenzuela-Stookey

This paper develops some mathematical models arising in behavioral sciences, particularly in psychology, which are formalized via general preferences with variable ordering structures. Our considerations are based on the recent variational…

Optimization and Control · Mathematics 2013-11-26 T. Q. Bao , B. S. Mordukhovich , A. Soubeyran

Given data on the choices made by consumers for different offer sets, a key challenge is to develop parsimonious models that describe and predict consumer choice behavior while being amenable to prescriptive tasks such as pricing and…

Machine Learning · Statistics 2025-04-15 Yanqiu Ruan , Xiaobo Li , Karthyek Murthy , Karthik Natarajan
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