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Related papers: Continuity and Monotonicity of Preferences and Pro…

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Theorem 1 in Bikhchandani & Segal (2011; Theoretical Economics) suggests that a complete, transitive, monotonic, and continuous preference is regret based if and only if it is expected utility. Their Proposition 1 suggests that transitivity…

Theoretical Economics · Economics 2024-07-02 Yuan Chang , Shuo Li Liu

Monotonicity and recursivity are central assumptions in intertemporal consumption problems under ambiguity. We show that monotone recursive preferences admit both a recursive and an ex-ante representation, and that the certainty equivalent…

Theoretical Economics · Economics 2026-01-23 Massimo Marinacci , Giulio Principi , Lorenzo Stanca

Nontransitive choices have long been an area of curiosity within economics. However, determining whether nontransitive choices represent an individual's preference is a difficult task since choice data is inherently stochastic. This paper…

Theoretical Economics · Economics 2023-05-01 Mogens Fosgerau , John Rehbeck

We consider methods for aggregating preferences that are based on the resolution of discrete optimization problems. The preferences are represented by arbitrary binary relations (possibly weighted) or incomplete paired comparison matrices.…

Optimization and Control · Mathematics 2007-05-23 Pavel Chebotarev , Elena Shamis

We study here preference revision, considering both the monotonic case where the original preferences are preserved and the nonmonotonic case where the new preferences may override the original ones. We use a relational framework in which…

Databases · Computer Science 2007-05-23 Jan Chomicki , Joyce Song

We extend well-known comparative results under expected utility to models of non-expected utility by providing novel conditions on local utility functions. We illustrate how our results parallel, and are distinct from, existing results for…

Theoretical Economics · Economics 2026-01-16 Collin Raymond , Yangwei Song

We provide an axiomatic characterization of lexicographic preferences over the set of all random availability functions using two assumptions. The first assumption is strong monotonicity, which in our framework is equivalent to the strong…

Theoretical Economics · Economics 2025-11-03 Somdeb Lahiri

We study the robustness of Bayesian persuasion to uncertainty about the receiver's preferences. We analyze two conceptually distinct notions: continuity, in which only the modeler lacks precise knowledge, but where the model's predictions…

Theoretical Economics · Economics 2026-05-28 Ronen Gradwohl , Fengming Hu , Rann Smorodinsky

The present paper investigates consequence relations that are both non-monotonic and paraconsistent. More precisely, we put the focus on preferential consequence relations, i.e. those relations that can be defined by a binary preference…

Artificial Intelligence · Computer Science 2007-05-23 Jonathan Ben-Naim

We propose a minimal yet intriguing model for a relationship between two individuals. The feeling of an individual is modeled by a complex variable and hence has two degrees of freedom. The effect of memory of other individual's behavior in…

Adaptation and Self-Organizing Systems · Physics 2023-08-17 Aarsh Chotalia , Shiva Dixit , P. Parmananda

We study preferences estimated from finite choice experiments and provide sufficient conditions for convergence to a unique underlying "true" preference. Our conditions are weak, and therefore valid in a wide range of economic environments.…

Theoretical Economics · Economics 2020-11-03 Christopher P. Chambers , Federico Echenique , Nicolas Lambert

Comparison-based preference learning has become central to the alignment of AI models with human preferences. However, these methods may behave counterintuitively. After empirically observing that, when accounting for a preference for…

In random expected utility (Gul and Pesendorfer, 2006), the distribution of preferences is uniquely recoverable from random choice. This paper shows through two examples that such uniqueness fails in general if risk preferences are random…

Theoretical Economics · Economics 2020-09-10 Yi-Hsuan Lin

Many prediction tasks can admit multiple models that can perform almost equally well. This phenomenon can can undermine interpretability and safety when competing models assign conflicting predictions to individuals. In this work, we study…

Machine Learning · Computer Science 2025-08-01 Erin George , Deanna Needell , Berk Ustun

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 analyse preference inference, through consistency, for general preference languages based on lexicographic models. We identify a property, which we call strong compositionality, that applies for many natural kinds of preference…

Logic in Computer Science · Computer Science 2024-11-01 Nic Wilson , Anne-Marie George

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

We elicit incomplete preferences over monetary gambles with subjective uncertainty. Subjects rank gambles, and these rankings are used to estimate preferences; payments are based on estimated preferences. About 40\% of subjects express…

General Economics · Economics 2022-10-06 Kirby Nielsen , Luca Rigotti

We establish an equivalence between two seemingly different theories: one is the traditional axiomatisation of incomplete preferences on horse lotteries based on the mixture independence axiom; the other is the theory of desirable gambles…

Artificial Intelligence · Computer Science 2018-01-03 Marco Zaffalon , Enrique Miranda

Recently, Halpern and Leung suggested representing uncertainty by a weighted set of probability measures, and suggested a way of making decisions based on this representation of uncertainty: maximizing weighted regret. Their paper does not…

Artificial Intelligence · Computer Science 2013-09-06 Joseph Y. Halpern
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