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We consider the problem of learning to perform a task from demonstrations given by teachers or experts, when some of the experts' demonstrations might be adversarial and demonstrate an incorrect way to perform the task. We propose a novel…

Machine Learning · Computer Science 2023-06-13 Prithviraj Dasgupta

We present an algorithm that identifies the reasoning patterns of agents in a game, by iteratively examining the graph structure of its Multi-Agent Influence Diagram (MAID) representation. If the decision of an agent participates in no…

Computer Science and Game Theory · Computer Science 2012-06-18 Dimitrios Antos , Avi Pfeffer

Business process deviance refers to the phenomenon whereby a subset of the executions of a business process deviate, in a negative or positive way, with respect to its expected or desirable outcomes. Deviant executions of a business process…

Artificial Intelligence · Computer Science 2016-08-31 Hoang Nguyen , Marlon Dumas , Marcello La Rosa , Fabrizio Maria Maggi , Suriadi Suriadi

We consider multi-player graph games with partial-observation and parity objective. While the decision problem for three-player games with a coalition of the first and second players against the third player is undecidable, we present a…

Logic in Computer Science · Computer Science 2014-04-23 Krishnendu Chatterjee , Laurent Doyen

Extra-Sensory Perception (ESP) cheats, which reveal hidden in-game information such as enemy locations, are difficult to detect because their effects are not directly observable in player behavior. The lack of observable evidence makes it…

Machine Learning · Computer Science 2026-01-01 Inkyu Park , Jeong-Gwan Lee , Taehwan Kwon , Juheon Choi , Seungku Kim , Junsu Kim , Kimin Lee

In multiple domains such as malware detection, automated driving systems, or fraud detection, classification algorithms are susceptible to being attacked by malicious agents willing to perturb the value of instance covariates to pursue…

Machine Learning · Statistics 2025-07-10 Victor Gallego , Roi Naveiro , Alberto Redondo , David Rios Insua , Fabrizio Ruggeri

This work introduces a unified framework for analyzing games in greater depth. In the existing literature, players' strategies are typically assigned scalar values, and equilibrium concepts are used to identify compatible choices. However,…

Computer Science and Game Theory · Computer Science 2026-02-04 Melih İşeri , Erhan Bayraktar

In centralized mechanisms and platforms, participants do not fully observe each others' type reports. Hence, if there is a deviation from the promised mechanism, participants may be unable to detect it. We formalize a notion of auditabilty…

Theoretical Economics · Economics 2024-05-20 Aram Grigoryan , Markus Möller

We compare games under delayed control and delay games, two types of infinite games modelling asynchronicity in reactive synthesis. In games under delayed control both players suffer from partial informedness due to symmetrically delayed…

Computer Science and Game Theory · Computer Science 2025-03-19 Martin Fränzle , Paul Kröger , Sarah Winter , Martin Zimmermann

The possibility of using player engagement predictions to profile high spending video game users is explored. In particular, individual-player survival curves in terms of days after first login, game level reached and accumulated playtime…

Machine Learning · Computer Science 2020-03-10 Ana Fernández del Río , Pei Pei Chen , África Periáñez

It is common to make a distinction between "strategic" behavior and other forms of intentional but "nonstrategic" behavior: typically, that strategic agents model other agents while nonstrategic agents do not. However, a crisp boundary…

Computer Science and Game Theory · Computer Science 2025-02-12 James R. Wright , Kevin Leyton-Brown

Deceptive patterns are often used in interface design to manipulate users into taking actions they would not otherwise take, such as consenting to excessive data collection. We present Trickery, a narrative serious game that incorporates…

Human-Computer Interaction · Computer Science 2024-10-25 Kirill Kronhardt , Kevin Rolfes , Jens Gerken

Strategic deception is an act of manipulating the opponent's perception to gain strategic advantages. In this paper, we study synthesis of deceptive winning strategies in two-player turn-based zero-sum reachability games on graphs with…

Computer Science and Game Theory · Computer Science 2021-04-26 Abhishek N. Kulkarni , Jie Fu

Imitation is simple behavior which uses successful actions of others in order to deal with one's own problems. Because success of imitation generally depends on whether profit of an imitating agent coincides with those of other agents or…

Physics and Society · Physics 2023-01-23 Masahiko Ueda

Motivated by applications where privacy is important, we consider planning problems for robots acting in the presence of an observer. We first formulate and then solve planning problems subject to stipulations on the information divulged…

Robotics · Computer Science 2019-07-19 Yulin Zhang , Dylan A. Shell , Jason M. O'Kane

We investigate how distorted, yet structured, beliefs can persist in strategic situations. Specifically, we study two-player games in which each player is endowed with a biased-belief function that represents the discrepancy between a…

Theoretical Economics · Economics 2020-06-30 Yuval Heller , Eyal Winter

In this paper, we employ a game-theoretic model to analyze the interaction between an adversary and a classifier. There are two classes (i.e., positive and negative classes) to which data points can belong. The adversary is interested in…

Cryptography and Security · Computer Science 2019-06-25 Farhad Farokhi

Our aim is to design mechanisms that motivate all agents to reveal their predictions truthfully and promptly. For myopic agents, proper scoring rules induce truthfulness. However, as has been described in the literature, when agents take…

Computer Science and Game Theory · Computer Science 2019-12-05 Amir Ban

Players are statistical learners who learn about payoffs from data. They may interpret the same data differently, but have common knowledge of a class of learning procedures. I propose a metric for the analyst's "confidence" in a strategic…

Theoretical Economics · Economics 2020-07-13 Annie Liang

Learning causal relationships between pairs of complex traits from observational studies is of great interest across various scientific domains. However, most existing methods assume the absence of unmeasured confounding and restrict causal…

Methodology · Statistics 2024-07-17 Wei Li , Rui Duan , Sai Li