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Concept drift refers to the change of data distributions over time. While drift poses a challenge for learning models, requiring their continual adaption, it is also relevant in system monitoring to detect malfunctions, system failures, and…

Machine Learning · Computer Science 2025-02-07 Fabian Hinder , Valerie Vaquet , Barbara Hammer

We consider games played on finite graphs, whose goal is to obtain a trace belonging to a given set of winning traces. We focus on those states from which Player 1 cannot force a win. We explore and compare several criteria for establishing…

Computer Science and Game Theory · Computer Science 2008-11-12 Marco Faella

Strategic classification studies the problem where self-interested individuals or agents manipulate their response to obtain favorable decision outcomes made by classifiers, typically turning to dishonest actions when they are less costly…

Machine Learning · Computer Science 2026-05-07 Ziyuan Huang , Lina Alkarmi , Mingyan Liu

We consider the problem of learning to exploit learning algorithms through repeated interactions in games. Specifically, we focus on the case of repeated two player, finite-action games, in which an optimizer aims to steer a no-regret…

Computer Science and Game Theory · Computer Science 2025-05-29 Yizhou Zhang , Yi-An Ma , Eric Mazumdar

In numerous positional games the identity of the winner is easily determined. In this case one of the more interesting questions is not {\em who} wins but rather {\em how fast} can one win. These type of problems were studied earlier for…

Combinatorics · Mathematics 2008-06-03 Dan Hefetz , Michael Krivelevich , Miloš Stojaković , Tibor Szabó

A planner aims to target individuals who exceed a threshold in a characteristic, such as wealth or ability. The individuals can rank their friends according to the characteristic. We study a strategy-proof mechanism for the planner to use…

General Economics · Economics 2021-01-11 Francis Bloch , Matthew Olckers

In dynamic noncooperative games, each player makes conjectures about other players' reactions before choosing a strategy. However, resulting equilibria may be multiple and do not always lead to desirable outcomes. These issues are typically…

Computer Science and Game Theory · Computer Science 2025-11-24 Francesco Morri , Hélène Le Cadre , David Salas , Didier Aussel

In this article we address two related issues on the learning of probabilistic sequences of events. First, which features make the sequence of events generated by a stochastic chain more difficult to predict. Second, how to model the…

Stance detection determines whether the author of a piece of text is in favor of, against, or neutral towards a specified target, and can be used to gain valuable insights into social media. The ubiquitous indirect referral of targets makes…

Computation and Language · Computer Science 2023-06-01 Zhengyuan Liu , Yong Keong Yap , Hai Leong Chieu , Nancy F. Chen

Distributed decision-makers are modeled as players in a game with two levels. High level decisions concern the game environment and determine the willingness of the players to form a coalition (or group). Low level decisions involve the…

Computer Science and Game Theory · Computer Science 2013-02-28 Edward A. Billard

Attack detection is usually approached as a classification problem. However, standard classification tools often perform poorly because an adaptive attacker can shape his attacks in response to the algorithm. This has led to the recent…

Computer Science and Game Theory · Computer Science 2017-06-26 Lemonia Dritsoula , Patrick Loiseau , John Musacchio

Understanding player strategies is a key question when analyzing player behavior both for academic researchers and industry practitioners. For game designers and game user researchers, it is important to gauge the distance between intended…

Human-Computer Interaction · Computer Science 2021-06-28 Truong-Huy Dinh Nguyen , Magy Seif El-Nasr , Alessandro Canossa

Perimeter identification involves ascertaining the boundaries of a designated area or zone, requiring traffic flow monitoring, control, or optimization. Various methodologies and technologies exist for accurately defining these perimeters;…

Artificial Intelligence · Computer Science 2024-09-06 Ayal Taitler

Conditions are presented for different types of identifiability of discrete variable models generated over an undirected graph in which one node represents a binary hidden variable. These models can be seen as extensions of the latent class…

Methodology · Statistics 2013-12-12 Elena Stanghellini , Barbara Vantaggi

We consider two-player games with imperfect information and the synthesis of a randomized strategy for one player that ensures the objective is satisfied almost-surely (i.e., with probability 1), regardless of the strategy of the other…

Computer Science and Game Theory · Computer Science 2024-07-30 Laurent Doyen , Thomas Soullard

Robots deployed to the real world must be able to interact with other agents in their environment. Dynamic game theory provides a powerful mathematical framework for modeling scenarios in which agents have individual objectives and…

In baseball, a scouting report profiles a player's characteristics and traits, usually intended for use in player valuation. This work presents a first-of-its-kind dataset of almost 10,000 scouting reports for minor league, international,…

Computation and Language · Computer Science 2019-10-29 Jacob Danovitch

An important feature of a dynamic game is its monitoring structure namely, what the players effectively see from the played actions. We consider games with arbitrary monitoring structures. One of the purposes of this paper is to know to…

Information Theory · Computer Science 2012-10-24 Maël Le Treust , Samson Lasaulce

This paper concerns the probabilistic evaluation of the effects of actions in the presence of unmeasured variables. We show that the identification of causal effect between a singleton variable X and a set of variables Y can be accomplished…

Artificial Intelligence · Computer Science 2013-02-21 David Galles , Judea Pearl

We present a technique for learning how to solve a multi-robot mission that requires interaction with an external environment by observing an expert system executing the same mission. We define the expert system as a team of robots equipped…