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We begin by formulating and characterizing a dominance criterion for prize sequences: $x$ dominates $y$ if any impatient agent prefers $x$ to $y$. With this in hand, we define a notion of comparative patience. Alice is more patient than Bob…

Theoretical Economics · Economics 2024-07-03 Mark Whitmeyer

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 analyze the problem of defining well-founded semantics for ordered logic programs within a general framework based on alternating fixpoint theory. We start by showing that generalizations of existing answer set approaches to preference…

Artificial Intelligence · Computer Science 2007-05-23 Torsten Schaub , Kewen Wang

Prompt-based methods have become increasingly popular among information extraction tasks, especially in low-data scenarios. By formatting a finetune task into a pre-training objective, prompt-based methods resolve the data scarce problem…

Computation and Language · Computer Science 2022-10-05 Jiaju Lin , Jie Zhou , Qin Chen

Surprisal theory links human processing effort to the predictability of an upcoming linguistic unit, but empirical work often leaves the notion of a unit underspecified. In practice, experimental stimuli are segmented into linguistically…

Computation and Language · Computer Science 2026-05-01 Samuel Kiegeland , Vésteinn Snæbjarnarson , Tim Vieira , Ryan Cotterell

We describe some recent approaches to score-based explanations for query answers in databases and outcomes from classification models in machine learning. The focus is on work done by the author and collaborators. Special emphasis is placed…

Artificial Intelligence · Computer Science 2021-09-21 Leopoldo Bertossi

We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility…

Artificial Intelligence · Computer Science 2016-08-31 Nir Friedman , Joseph Y. Halpern

Starting with a likelihood or preference order on worlds, we extend it to a likelihood ordering on sets of worlds in a natural way, and examine the resulting logic. Lewis earlier considered such a notion of relative likelihood in the…

Artificial Intelligence · Computer Science 2016-08-31 J. Y. Halpern

The rule "defeated(X) $\leftarrow$ attacks(Y,X), $\neg$ defeated(Y)" states that an argument is defeated if it is attacked by an argument that is not defeated. The rule "win(X) $\leftarrow$ move(X,Y), $\neg$ win(Y)" states that in a game a…

Logic in Computer Science · Computer Science 2023-09-14 Bertram Ludäscher , Yilin Xia

In order to enrich dynamic semantic theories with a `pragmatic' capacity, we combine dynamic and nonmonotonic (preferential) logics in a modal logic setting. We extend a fragment of Van Benthem and De Rijke's dynamic modal logic with…

cmp-lg · Computer Science 2008-02-03 Jan Jaspars , Megumi Kameyama

When composing multiple preferences characterizing the most suitable results for a user, several issues may arise. Indeed, preferences can be partially contradictory, suffer from a mismatch with the level of detail of the actual data, and…

Databases · Computer Science 2025-01-10 Paolo Ciaccia , Davide Martinenghi , Riccardo Torlone

This paper investigates the problem of finding a preference relation on a set of acts from the knowledge of an ordering on events (subsets of states of the world) describing the decision-maker (DM)s uncertainty and an ordering of…

Artificial Intelligence · Computer Science 2013-02-08 Didier Dubois , Helene Fargier , Henri Prade

Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly…

Artificial Intelligence · Computer Science 2021-08-10 Tuomo Lehtonen , Johannes P. Wallner , Matti Järvisalo

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

Classification problems in security settings are usually contemplated as confrontations in which one or more adversaries try to fool a classifier to obtain a benefit. Most approaches to such adversarial classification problems have focused…

Machine Learning · Statistics 2019-09-25 Roi Naveiro , Alberto Redondo , David Ríos Insua , Fabrizio Ruggeri

Drawing appropriate defeasible inferences has been proven to be one of the most pervasive puzzles of natural language processing and a recurrent problem in pragmatics. This paper provides a theoretical framework, called ``stratified…

cmp-lg · Computer Science 2008-02-03 Daniel Marcu , Graeme Hirst

We provide a semantic framework for preference handling in answer set programming. To this end, we introduce preference preserving consequence operators. The resulting fixpoint characterizations provide us with a uniform semantic framework…

Artificial Intelligence · Computer Science 2007-05-23 Torsten Schaub , Kewen Wang

Comparison and contrast are the basic means to unveil causation and learn which treatments work. To build good comparison groups, randomized experimentation is key, yet often infeasible. In such non-experimental settings, we illustrate and…

Methodology · Statistics 2024-01-30 Ambarish Chattopadhyay , Jose R. Zubizarreta

Individual choices often depend on the order in which the decisions are made. In this paper, we expose a general theory of measurable systems (an example of which is an individual's preferences) allowing for incompatible (non-commuting)…

Physics and Society · Physics 2007-06-20 V. I. Danilov , A. Lambert-Mogiliansky

Value-based argumentation enhances a classical abstract argumentation graph - in which arguments are modelled as nodes connected by directed arrows called attacks - with labels on arguments, called values, and an ordering on values, called…

Multiagent Systems · Computer Science 2019-07-23 Grzegorz Lisowski , Sylvie Doutre , Umberto Grandi