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Related papers: An AGM Approach to Revising Preferences

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Belief revision of knowledge bases represented by a set of sentences in a given logic has been extensively studied but for specific logics, mainly propositional, and also recently Horn and description logics. Here, we propose to generalize…

Artificial Intelligence · Computer Science 2017-01-17 Marc Aiguier , Jamal Atif , Isabelle Bloch , Céline Hudelot

A critical issue in the evolution of software models is change propagation: given a primary change that is made to a model in order to meet a new or changed requirement, what additional secondary changes are needed to maintain consistency…

Software Engineering · Computer Science 2014-02-26 Hoa Khanh Dam , Aditya Ghose

In this work we generalize standard Decision Theory by assuming that two outcomes can also be incomparable. Two motivating scenarios show how incomparability may be helpful to represent those situations where, due to lack of information,…

Computer Science and Game Theory · Computer Science 2014-04-04 Piero A. Bonatti , Marco Faella , Luigi Sauro

Limited by cognitive abilities, decision-makers (DMs) may struggle to evaluate decision alternatives based on all criteria in multiple criteria decision-making problems. This paper proposes an embedded criteria selection method derived from…

Optimization and Control · Mathematics 2025-06-10 Kun Zhou , Zaiwu Gong , Guo Wei , Roman Slowinski

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 propose a new approach to belief revision that provides a way to change knowledge bases with a minimum of effort. We call this way of revising belief states optimal belief revision. Our revision method gives special attention to the fact…

Artificial Intelligence · Computer Science 2007-05-23 Carmen Vodislav , Robert E. Mercer

Accommodating human preferences is essential for creating AI agents that deliver personalized and effective interactions. Recent work has shown the potential for LLMs to infer preferences from user interactions, but they often produce broad…

Artificial Intelligence · Computer Science 2024-10-10 Stephane Aroca-Ouellette , Natalie Mackraz , Barry-John Theobald , Katherine Metcalf

Reward modelling from preference data is a crucial step in aligning large language models (LLMs) with human values, requiring robust generalisation to novel prompt-response pairs. In this work, we propose to frame this problem in a causal…

Artificial Intelligence · Computer Science 2026-05-12 Katarzyna Kobalczyk , Mihaela van der Schaar

Background: Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical…

Physics and Society · Physics 2014-11-18 A. E. Allahverdyan , Aram Galstyan

In the classic AGM belief revision theory, beliefs are static and do not change their own shape. For instance, if p is accepted by a rational agent, it will remain p to the agent. But such rarely happens to us. Often, when we accept some…

Artificial Intelligence · Computer Science 2016-01-28 Ryuta Arisaka

We propose and develop an algebraic approach to revealed preference. Our approach dispenses with non algebraic structure, such as topological assumptions. We provide algebraic axioms of revealed preference that subsume previous, classical…

Theoretical Economics · Economics 2021-06-01 Mikhail Freer , Cesar Martinelli

We present a general logical framework for reasoning about agents' cognitive attitudes of both epistemic type and motivational type. We show that it allows us to express a variety of relevant concepts for qualitative decision theory…

Artificial Intelligence · Computer Science 2023-06-22 Emiliano Lorini

When using LLMs to rank items based on given criteria, or evaluate answers, the order of candidate items can influence the model's final decision. This sensitivity to item positioning in a LLM's prompt is known as position bias. Prior…

Machine Learning · Computer Science 2025-07-25 Ali Vardasbi , Gustavo Penha , Claudia Hauff , Hugues Bouchard

This paper reports a modified axiomatic foundation of the analytic hierarchy process (AHP), where the reciprocal property of paired comparisons is broken. The novel concept of reciprocal symmetry breaking is proposed to characterize the…

Information Theory · Computer Science 2021-08-05 Fang Liu , Wei-Guo Zhang

The field of iterated belief change has focused mainly on revision, with the other main operator of AGM belief change theory, i.e. contraction, receiving relatively little attention. In this paper we extend the Harper Identity from…

Artificial Intelligence · Computer Science 2016-04-20 Jake Chandler , Richard Booth

Understanding citizens' values in participatory systems is crucial for citizen-centric policy-making. We envision a hybrid participatory system where participants make choices and provide motivations for those choices, and AI agents…

Artificial Intelligence · Computer Science 2025-02-12 Enrico Liscio , Luciano C. Siebert , Catholijn M. Jonker , Pradeep K. Murukannaiah

Belief change is a fundamental problem in AI: Agents constantly have to update their beliefs to accommodate new observations. In recent years, there has been much work on axiomatic characterizations of belief change. We claim that a better…

Artificial Intelligence · Computer Science 2007-05-23 Nir Friedman , Joseph Y. Halpern

Several rules for social choice are examined from a unifying point of view that looks at them as procedures for revising a system of degrees of belief in accordance with certain specified logical constraints. Belief is here a social…

Artificial Intelligence · Computer Science 2015-05-06 Rosa Camps , Xavier Mora , Laia Saumell

Automated negotiation in complex, multi-party and multi-issue settings critically depends on accurate opponent modeling. However, conventional numerical-only approaches fail to capture the qualitative information embedded in natural…

Argumentation is a promising model for reasoning with uncertain knowledge. The key concept of acceptability enables to differentiate arguments and counterarguments: The certainty of a proposition can then be evaluated through the most…

Artificial Intelligence · Computer Science 2013-02-01 Leila Amgoud , Claudette Cayrol