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This paper considers the task of learning users' preferences on a combinatorial set of alternatives, as generally used by online configurators, for example. In many settings, only a set of selected alternatives during past interactions is…

Artificial Intelligence · Computer Science 2022-09-26 Hélène Fargier , Pierre-François Gimenez , Jérôme Mengin , Bao Ngoc Le Nguyen

We bound features of counterfactual choices in the nonparametric random utility model of demand, i.e. if observable choices are repeated cross-sections and one allows for unrestricted, unobserved heterogeneity. In this setting, tight bounds…

Econometrics · Economics 2019-05-21 Yuichi Kitamura , Jörg Stoye

A family of models of individual discrete choice are constructed by means of statistical averaging of choices made by a subject in a reinforcement learning process, where the subject has short, k-term memory span. The choice probabilities…

Econometrics · Economics 2019-08-20 Misha Perepelitsa

In several matching markets, in order to achieve diversity, agents' priorities are allowed to vary across an institution's available seats, and the institution is let to choose agents in a lexicographic fashion based on a predetermined…

Theoretical Economics · Economics 2019-10-30 Battal Dogan , Serhat Dogan , Kemal Yildiz

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 extend the work of Antunovi\'{c}, Mossel and R\'{a}cz on competing types in preferential attachment models to include cases where the types have different fitnesses, which may be either multiplicative or additive. We will show that,…

Probability · Mathematics 2018-09-07 Jonathan Jordan

Probabilistic risk aversion, defined through quasi-convexity in probabilistic mixtures, is a common useful property in decision analysis. We study a general class of non-monotone mappings, called the generalized rank-dependent functions,…

Theoretical Economics · Economics 2024-09-30 Ruodu Wang , Qinyu Wu

In this paper, we study the effect of preferences in abstract argumentation under a claim-centric perspective. Recent work has revealed that semantical and computational properties can change when reasoning is performed on claim-level…

Artificial Intelligence · Computer Science 2022-04-29 Michael Bernreiter , Wolfgang Dvorak , Anna Rapberger , Stefan Woltran

This article introduces a framework for evaluating statistical decisions under both prior ambiguity and likelihood misspecification. We begin with an ambiguity set - a frequentist model that pairs a possibly misspecified likelihood with…

Econometrics · Economics 2026-05-14 Karun Adusumilli

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that typically arise from applying decision rules…

Artificial Intelligence · Computer Science 2018-06-05 Jasper De Bock , Gert de Cooman

Good quality explanations strengthen the understanding of language models and data. Feature attribution methods, such as Integrated Gradient, are a type of post-hoc explainer that can provide token-level insights. However, explanations on…

Computation and Language · Computer Science 2026-04-21 Jonathan Kamp , Roos Bakker , Dominique Blok

We consider social welfare functions that satisfy Arrow's classic axioms of independence of irrelevant alternatives and Pareto optimality when the outcome space is the convex hull of some finite set of alternatives. Individual and…

Computer Science and Game Theory · Computer Science 2019-04-15 Florian Brandl , Felix Brandt

We provide an axiomatic foundation for the representation of num\'{e}raire-invariant preferences of economic agents acting in a financial market. In a static environment, the simple axioms turn out to be equivalent to the following choice…

General Finance · Quantitative Finance 2010-11-09 Constantinos Kardaras

We propose an axiomatic approach which economically underpins the representation of dynamic preferences in terms of a stochastic utility function, sensitive to the information available to the decision maker. Our construction is iterative…

Probability · Mathematics 2020-02-24 Marco Maggis , Andrea Maran

We explore the influence of framing on decision-making, where some products are framed (e.g., displayed, recommended, endorsed, or labeled). We introduce a novel choice function that captures observed variations in framed alternatives.…

Theoretical Economics · Economics 2025-02-04 Paul H. Y. Cheung , Yusufcan Masatlioglu

Self-preference is a fundamental feature of biological organisms. Since large language models (LLMs) lack sentience, they might be expected to avoid such distortions. Yet, across 72 experiments and ~41,000 queries, we discovered massive…

Artificial Intelligence · Computer Science 2026-05-20 Steven A. Lehr , Mary Cipperman , Mahzarin R. Banaji

We study three axioms in the model of constrained social choice under uncertainty where (i) agents have subjective expected utility preferences over acts and (ii) different states of nature have (possibly) different sets of available…

Theoretical Economics · Economics 2024-08-05 Eric Bahel

An account of utterance interpretation in discourse needs to face the issue of how the discourse context controls the space of interacting preferences. Assuming a discourse processing architecture that distinguishes the grammar and…

cmp-lg · Computer Science 2008-02-03 Megumi Kameyama

Information about user preferences plays a key role in automated decision making. In many domains it is desirable to assess such preferences in a qualitative rather than quantitative way. In this paper, we propose a qualitative graphical…

Artificial Intelligence · Computer Science 2011-07-04 C. Boutilier , R. I. Brafman , C. Domshlak , H. H. Hoos , D. Poole

Distributions over rankings are used to model data in various settings such as preference analysis and political elections. The factorial size of the space of rankings, however, typically forces one to make structural assumptions, such as…

Machine Learning · Computer Science 2012-02-20 Jonathan Huang , Ashish Kapoor , Carlos E. Guestrin