English
Related papers

Related papers: The shape of incomplete preferences

200 papers

Approaches to decision-making under uncertainty in the belief function framework are reviewed. Most methods are shown to blend criteria for decision under ignorance with the maximum expected utility principle of Bayesian decision theory. A…

Artificial Intelligence · Computer Science 2019-12-13 Thierry Denoeux

We propose a model of incomplete \textit{twofold multiprior preferences}, in which an act $f$ is ranked above an act $g$ only when $f$ provides higher utility in a worst-case scenario than what $g$ provides in a best-case scenario. The…

Theoretical Economics · Economics 2022-01-14 Federico Echenique , Masaki Miyashita , Yuta Nakamura , Luciano Pomatto , Jamie Vinson

One of the exciting developments in the stated preference literature is the use of probabilistic stated preference experiments to estimate semi-parametric population distributions of ex ante returns and willingness-to-pay (WTP) for a choice…

Econometrics · Economics 2025-05-09 Romuald Meango , Esther Mirjam Girsberger

This paper presents an advance in the direction of working with probabilities in a paracomplete setting using Logics of Formal Undeterminedness (LFUs). The undeterminedness is interpreted here as missing evidence. A theorem of total…

Logic · Mathematics 2025-07-08 Sankha S. Basu , Esha Jain

Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat other domain attributes: as a random variable with a density…

Artificial Intelligence · Computer Science 2013-01-18 Urszula Chajewska , Daphne Koller

Preferential sampling is a common feature in geostatistics and occurs when the locations to be sampled are chosen based on information about the phenomena under study. In this case, point pattern models are commonly used as the probability…

Methodology · Statistics 2022-10-27 Douglas Mateus da Silva , Dani Gamerman

Relational data are usually highly incomplete in practice, which inspires us to leverage side information to improve the performance of community detection and link prediction. This paper presents a Bayesian probabilistic approach that…

Machine Learning · Statistics 2017-06-15 He Zhao , Lan Du , Wray Buntine

Quantum uncertainty relations impose fundamental limits on the joint knowledge that can be acquired from complementary observables: perfect knowledge of a quantum state in one basis implies maximal indetermination in all other mutually…

To determine the welfare implications of price changes in demand data, we introduce a revealed preference relation over prices. We show that the absence of cycles in this relation characterizes a consumer who trades off the utility of…

Econometrics · Economics 2024-07-03 Rahul Deb , Yuichi Kitamura , John K. -H. Quah , Jörg Stoye

In Basili and Pratelli (2024), a novel and coherent concept of interval probability measures has been introduced, providing a method for representing imprecise probabilities and uncertainty. Within the framework of set algebra, we…

Statistics Theory · Mathematics 2024-04-25 Marcello Basili , Luca Pratelli

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 demonstrate that incomplete quantum tomography can give conclusive information in experimental realizations. We divide the state space into a union of multiple disjoint subsets and determine conclusively which of the subsets a system,…

Quantum Physics · Physics 2019-05-03 Henri Lyyra , Tom Kuusela , Teiko Heinosaari

Relative entropy (divergence) of Bregman type recently proposed by T. D. Frank and Jan Naudts is considered and its quantum counterpart is used to calculate purity of the Werner state in nonextensive formalism. It has been observed that two…

Statistical Mechanics · Physics 2009-11-11 Gokhan B. Bagci , Altug Arda , Ramazan Sever

This paper advocates the usefulness of new theories of uncertainty for the purpose of modeling some facets of uncertain knowledge, especially vagueness, in AI. It can be viewed as a partial reply to Cheeseman's (among others) defense of…

Artificial Intelligence · Computer Science 2013-04-10 Didier Dubois , Henri Prade

Utility representations of preference relations in symmetric topological spaces have the advantage of fully characterising these relations. But, this is not true in the case of representations of preference relations that are mostly…

General Topology · Mathematics 2023-04-07 Athanasios Andrikopoulos

There has been an ever-increasing interest in multidisciplinary research on representing and reasoning with imperfect data. Possibilistic networks present one of the powerful frameworks of interest for representing uncertain and imprecise…

Artificial Intelligence · Computer Science 2016-07-14 Maroua Haddad , Philippe Leray , Nahla Ben Amor

We propose a class of semimetrics for preference relations any one of which is an alternative to the classical Kemeny-Snell-Bogart metric. (We take a fairly general viewpoint about what constitutes a preference relation, allowing for any…

Combinatorics · Mathematics 2022-03-10 Hiroki Nishimura , Efe A. Ok

The paper deals with partial and weak preference relations defined on infinite-dimensional vector spaces and compatible with algebraic operations. By a partial preference we mean an asymmetric and transitive binary relation, while a weak…

Optimization and Control · Mathematics 2024-01-17 V. V. Gorokhovik

We study a continuous-time portfolio choice problem for an investor whose state-dependent preferences are determined by an exogenous factor that evolves as an It\^o diffusion process. Since risk attitudes at the end of the investment…

Mathematical Finance · Quantitative Finance 2025-12-25 Luca De Gennaro Aquino , Sascha Desmettre , Yevhen Havrylenko , Mogens Steffensen

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