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A reciprocal recommendation problem is one where the goal of learning is not just to predict a user's preference towards a passive item (e.g., a book), but to recommend the targeted user on one side another user from the other side such…

Machine Learning · Computer Science 2018-06-05 Fabio Vitale , Nikos Parotsidis , Claudio Gentile

Understanding what leads to effective conversations can aid the design of better computer-mediated communication platforms. In particular, prior observational work has sought to identify behaviors of individuals that correlate to their…

Computation and Language · Computer Science 2020-09-10 Justine Zhang , Sendhil Mullainathan , Cristian Danescu-Niculescu-Mizil

Decision trees are simple, yet powerful, classification models used to classify categorical and numerical data, and, despite their simplicity, they are commonly used in operations research and management, as well as in knowledge mining.…

Logic in Computer Science · Computer Science 2020-03-13 Andrea Brunello , Guido Sciavicco , Ionel Eduard Stan

Patterns are words with terminals and variables. The language of a pattern is the set of words obtained by uniformly substituting all variables with words that contain only terminals. In their original definition, patterns only allow for…

Formal Languages and Automata Theory · Computer Science 2026-03-31 Klaus Jansen , Dirk Nowotka , Lis Pirotton , Corinna Wambsganz , Max Wiedenhöft

We explore the connection between an agent's decision problem and her ranking of information structures. We find that a finite amount of ordinal data on the agent's ranking of experiments is enough to identify her (finite) set of…

Theoretical Economics · Economics 2024-04-02 Mark Whitmeyer

This paper examines two related problems that are central to developing an autonomous decision-making agent, such as a robot. Both problems require generating structured representafions from a database of unstructured declarative knowledge…

Artificial Intelligence · Computer Science 2013-04-10 Spencer Star

Ranking is one of the most fundamental problems in machine learning with applications in many branches of computer science such as: information retrieval systems, recommendation systems, machine translation and computational biology.…

Data Structures and Algorithms · Computer Science 2015-04-07 Krzysztof Choromanski

This paper uses category theory to develop an entirely new approach to approximate game theory. Game theory is the study of how different agents within a multi-agent system take decisions. At its core, game theory asks what an optimal…

Computer Science and Game Theory · Computer Science 2025-09-26 Neil Ghani

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

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 (1973) earlier considered such a notion of relative likelihood in the…

Artificial Intelligence · Computer Science 2014-07-29 Joseph Y. Halpern

An algebraic formalism for the study of interacting particle systems is developed. Particle processes are described in terms of the category theory. The problem for the unique description of these processes is discussed. Categories relevant…

Quantum Algebra · Mathematics 2007-05-23 Wladyslaw Marcinek

Planning with preferences has been employed extensively to quickly generate high-quality plans. However, it may be difficult for the human expert to supply this information without knowledge of the reasoning employed by the planner and the…

Artificial Intelligence · Computer Science 2018-04-23 Mayukh Das , Phillip Odom , Md. Rakibul Islam , Janardhan Rao , Doppa , Dan Roth , Sriraam Natarajan

In multi-objective decision planning and learning, much attention is paid to producing optimal solution sets that contain an optimal policy for every possible user preference profile. We argue that the step that follows, i.e, determining…

Machine Learning · Computer Science 2018-02-22 Luisa M Zintgraf , Diederik M Roijers , Sjoerd Linders , Catholijn M Jonker , Ann Nowé

The purpose of this short paper is to identify the mathematical essence of the superiorization methodology. This methodology has been developed in recent years while attempting to solve specific application-oriented problems. Consequently,…

Optimization and Control · Mathematics 2019-09-20 Gabor T. Herman

We develop a qualitative model of decision making with two aims: to describe how people make simple decisions and to enable computer programs to do the same. Current approaches based on Planning or Decisions Theory either ignore uncertainty…

Artificial Intelligence · Computer Science 2013-02-18 Blai Bonet , Hector Geffner

Evolutionary game theory assumes that individuals maximize their benefits when choosing strategies. However, an alternative perspective proposes that individuals seek to maximize the benefits of others. To explore the relationship between…

Physics and Society · Physics 2024-05-16 Chaoqian Wang , Attila Szolnoki

Experts advising decision-makers are likely to display expertise which varies as a function of the problem instance. In practice, this may lead to sub-optimal or discriminatory decisions against minority cases. In this work we model such…

Artificial Intelligence · Computer Science 2023-10-27 Axel Abels , Tom Lenaerts , Vito Trianni , Ann Nowé

In this paper we extend the principle of proportional representation to rankings. We consider the setting where alternatives need to be ranked based on approval preferences. In this setting, proportional representation requires that…

Computer Science and Game Theory · Computer Science 2016-12-06 Piotr Skowron , Martin Lackner , Markus Brill , Dominik Peters , Edith Elkind

The primary theme of this investigation is a decision theoretic account of conditional ought statements (e.g., "You ought to do A, if C") that rectifies glaring deficiencies in classical deontic logic. The resulting account forms a sound…

Artificial Intelligence · Computer Science 2013-03-08 Judea Pearl

This paper addresses decision-aiding problems that involve multiple objectives and uncertain states of the world. Inspired by the capability approach, we focus on cases where a policy maker chooses an act that, combined with a state of the…

Computers and Society · Computer Science 2024-05-24 Nicolas Fayard , David Ríos Insua , Alexis Tsoukiàs
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