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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

If uncertainty is modelled by a probability measure, decisions are typically made by choosing the option with the highest expected utility. If an imprecise probability model is used instead, this decision rule can be generalised in several…

Artificial Intelligence · Computer Science 2020-03-27 Jasper De Bock

Methods for choosing from a set of options are often based on a strict partial order on these options, or on a set of such partial orders. I here provide a very general axiomatic characterisation for choice functions of this form. It…

Artificial Intelligence · Computer Science 2020-04-03 Jasper De Bock

We identify the (filter representation of the) logic behind the recent theory of coherent sets of desirable (sets of) things, which generalise coherent sets of desirable (sets of) gambles as well as coherent choice functions, and show that…

Logic · Mathematics 2024-06-21 Gert de Cooman , Arthur Van Camp , Jasper De Bock

The desirable gambles framework provides a foundational approach to imprecise probability theory but relies heavily on linear utility assumptions. This paper introduces function-coherent gambles, a generalization that accommodates…

Theoretical Economics · Economics 2025-04-28 Gregory Wheeler

Coherent sets of desirable gamble sets is used as a model for representing an agents opinions and choice preferences under uncertainty. In this paper we provide some results about the axioms required for coherence and the natural extension…

Artificial Intelligence · Computer Science 2024-05-17 Catrin Campbell-Moore

We investigate how to model exchangeability with choice functions. Exchangeability is a structural assessment on a sequence of uncertain variables. We show how such assessments are a special indifference assessment, and how that leads to a…

Artificial Intelligence · Computer Science 2017-03-07 Arthur Van Camp , Gert de Cooman

We study how to infer new choices from previous choices in a conservative manner. To make such inferences, we use the theory of choice functions: a unifying mathematical framework for conservative decision making that allows one to impose…

Artificial Intelligence · Computer Science 2020-07-16 Arne Decadt , Jasper De Bock , Gert de Cooman

In a real expert system, one may have unreliable, unconfident, conflicting estimates of the value for a particular parameter. It is important for decision making that the information present in this aggregate somehow find its way into use.…

Artificial Intelligence · Computer Science 2013-04-15 Henry Hamburger

As the world's democratic institutions are challenged by dissatisfied citizens, political scientists and also computer scientists have proposed and analyzed various (innovative) methods to select representative bodies, a crucial task in…

Multiagent Systems · Computer Science 2023-04-07 Manon Revel , Niclas Boehmer , Rachael Colley , Markus Brill , Piotr Faliszewski , Edith Elkind

We advance a general theory of coherent preference that surrenders restrictions embodied in orthodox doctrine. This theory enjoys the property that any preference system admits extension to a complete system of preferences, provided it…

Probability · Mathematics 2025-08-04 Arthur Paul Pedersen , Samuel Allen Alexander

We introduce a logic specifically designed to support reasoning about social choice functions. The logic includes operators to capture strategic ability, and operators to capture agent preferences. We establish a correspondence between…

Multiagent Systems · Computer Science 2011-04-29 Nicolas Troquard , Wiebe van der Hoek , Michael Wooldridge

We present a new strategic voting model where we use uncertainty representation to model preferences. Specifically, we use probability sets as uncertainty representations, together with lower and upper expected utility gains to take…

Computer Science and Game Theory · Computer Science 2026-05-18 Henri Surugue , Sébastien Destercke

We study how to infer new choices from prior choices using the framework of choice functions, a unifying mathematical framework for decision-making based on sets of preference orders. In particular, we define the natural (most conservative)…

Artificial Intelligence · Computer Science 2024-12-02 Arne Decadt , Alexander Erreygers , Jasper De Bock

We derive axiomatically the probability function that should be used to make decisions given any form of underlying uncertainty.

Artificial Intelligence · Computer Science 2013-04-08 Philippe Smets

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The…

Computation and Language · Computer Science 2019-12-17 Mo Yu , Shiyu Chang , Yang Zhang , Tommi S. Jaakkola

When quantitative models are used to support decision-making on complex and important topics, understanding a model's ``reasoning'' can increase trust in its predictions, expose hidden biases, or reduce vulnerability to adversarial attacks.…

Machine Learning · Computer Science 2019-07-09 Dimitris Bertsimas , Arthur Delarue , Patrick Jaillet , Sebastien Martin

We consider the challenge of preference elicitation in systems that help users discover the most desirable item(s) within a given database. Past work on preference elicitation focused on structured models that provide a factored…

Artificial Intelligence · Computer Science 2012-07-19 Ronen I. Brafman , Carmel Domshlak , Tanya Kogan

People care about decision outcomes and how decisions get made, both when making decisions and reflecting on decisions. But formalizing the full range of normative concerns that drive decisions is an open challenge. We introduce Axiomatic…

Artificial Intelligence · Computer Science 2026-02-11 Ben Abramowitz , Nicholas Mattei

Choice modeling is at the core of understanding how changes to the competitive landscape affect consumer choices and reshape market equilibria. In this paper, we propose a fundamental characterization of choice functions that encompasses a…

Econometrics · Economics 2024-02-21 Amandeep Singh , Ye Liu , Hema Yoganarasimhan
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