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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

A class of discrete Bidding Combinatorial Games that generalize alternating normal play was introduced by Kant, Larsson, Rai, and Upasany (2022). The major questions concerning optimal outcomes were resolved. By generalizing standard game…

Computer Science and Game Theory · Computer Science 2023-10-31 Prem Kant , Urban Larsson , Ravi K. Rai , Akshay V. Upasany

We consider the problem of inferring an unknown ranking of $n$ items from a random tournament on $n$ vertices whose edge directions are correlated with the ranking. We establish, in terms of the strength of these correlations, the…

Statistics Theory · Mathematics 2024-07-24 Dmitriy Kunisky , Daniel A. Spielman , Xifan Yu

The study of IR evaluation metrics through axiomatic analysis enables a better understanding of their numerical properties. Some works have modelled the effectiveness of retrieval metrics with axioms that capture desirable properties on the…

Information Retrieval · Computer Science 2022-07-05 Fernando Giner

Previous work on the competitive retrieval setting focused on a single-query setting: document authors manipulate their documents so as to improve their future ranking for a given query. We study a competitive setting where authors opt to…

Information Retrieval · Computer Science 2024-04-16 Haya Nachimovsky , Moshe Tennenholtz , Fiana Raiber , Oren Kurland

Object ranking or "learning to rank" is an important problem in the realm of preference learning. On the basis of training data in the form of a set of rankings of objects represented as feature vectors, the goal is to learn a ranking…

Machine Learning · Statistics 2017-12-05 Mohsen Ahmadi Fahandar , Eyke Hüllermeier

Attribution methods reveal which input features a neural network uses for a prediction, adding transparency to their decisions. A common problem is that these attributions seem unspecific, highlighting both important and irrelevant…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Nils Philipp Walter , Jilles Vreeken , Jonas Fischer

The pairwise comparisons method is a convenient tool used when the relative order of preferences among different concepts (alternatives) needs to be determined. There are several popular implementations of this method, including the…

Discrete Mathematics · Computer Science 2018-02-08 Konrad Kułakowski

We present a preference learning framework for multiple criteria sorting. We consider sorting procedures applying an additive value model with diverse types of marginal value functions (including linear, piecewise-linear, splined, and…

Machine Learning · Computer Science 2019-10-15 Jiapeng Liu , Milosz Kadzinski , Xiuwu Liao , Xiaoxin Mao , Yao Wang

Adjoint logic is a general approach to combining multiple logics with different structural properties, including linear, affine, strict, and (ordinary) intuitionistic logics, where each proposition has an intrinsic mode of truth. It has…

Logic in Computer Science · Computer Science 2024-02-05 Junyoung Jang , Sophia Roshal , Frank Pfenning , Brigitte Pientka

We show that probabilistic equivalence of a regret-based preference relationship over random variables is implied by a weak form of continuity and monotonicity.

Theoretical Economics · Economics 2024-09-27 Sushil Bikhchandani , Uzi Segal

We consider a setting in which a principal gets to choose which game from some given set is played by a group of agents. The principal would like to choose a game that favors one of the players, the social preferences of the players, or the…

Computer Science and Game Theory · Computer Science 2025-11-27 Caspar Oesterheld , Vincent Conitzer

In this paper, we consider large-scale ranking problems where one is given a set of (possibly non-redundant) pairwise comparisons and the underlying ranking explained by those comparisons is desired. We show that stochastic gradient descent…

Optimization and Control · Mathematics 2024-07-04 Benjamin Jarman , Lara Kassab , Deanna Needell , Alexander Sietsema

We analyze a little-known property of apportionment methods that captures how allocations scale with the size of the house: specifically, if, for a fixed population distribution, the house size and allocation can be scaled down within the…

General Mathematics · Mathematics 2023-11-14 Michael A. Jones , David McCune , Jennifer M. Wilson

Most of the stochastic orders for comparing random variables, considered in the literature, are afflicted with two main drawbacks: (i) lack of connex property and (ii) lack of consideration of any dependence structure between the random…

Methodology · Statistics 2021-03-03 Sugata Ghosh , Asok K. Nanda

We study stable matching problems in networks where players are embedded in a social context, and may incorporate friendship relations or altruism into their decisions. Each player is a node in a social network and strives to form a good…

Computer Science and Game Theory · Computer Science 2012-04-27 Elliot Anshelevich , Onkar Bhardwaj , Martin Hoefer

The transitivity of preferences is one of the basic assumptions used in the theory of games and decisions. It is often equated with rationality of choice and is considered useful in building rankings. Intransitive preferences are considered…

Quantum Physics · Physics 2015-06-23 Marcin Makowski , Edward W. Piotrowski , Jan Sładkowski

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

To aggregate rankings into a social ranking, one can use scoring systems such as Plurality, Veto, and Borda. We distinguish three types of methods: ranking by score, ranking by repeatedly choosing a winner that we delete and rank at the…

Computer Science and Game Theory · Computer Science 2022-09-20 Niclas Boehmer , Robert Bredereck , Dominik Peters

Estimating consumer preferences is central to many problems in economics and marketing. This paper develops a flexible framework for learning individual preferences from partial ranking information by interpreting observed rankings as…

Machine Learning · Statistics 2026-02-19 Yu-Chang Chen , Chen Chian Fuh , Shang En Tsai