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Partial-monitoring games constitute a mathematical framework for sequential decision making problems with imperfect feedback: The learner repeatedly chooses an action, opponent responds with an outcome, and then the learner suffers a loss…

Computer Science and Game Theory · Computer Science 2011-10-13 András Antos , Gábor Bartók , Dávid Pál , Csaba Szepesvári

We study two natural problems about rational behaviors in multiplayer non-zero-sum sequential infinite duration games played on graphs: checking problems, that consist in deciding whether a strategy profile, defined by a Mealy machine, is…

Computer Science and Game Theory · Computer Science 2023-07-17 Léonard Brice , Jean-François Raskin , Marie van den Bogaard

In game theory and artificial intelligence, decision making models often involve maximizing expected utility, which does not respect ordinal invariance. In this paper, the author discusses the possibility of preserving ordinal invariance…

Artificial Intelligence · Computer Science 2010-06-14 Ji Han

To achieve desirable performance, current AI systems often require huge amounts of training data. This is especially problematic in domains where collecting data is both expensive and time-consuming, e.g., where AI systems require having…

Artificial Intelligence · Computer Science 2022-10-11 Ardavan S. Nobandegani , Thomas R. Shultz , Irina Rish

This work lies in the fusion of experimental economics and data mining. It continues author's previous work on mining behaviour rules of human subjects from experimental data, where game-theoretic predictions partially fail to work.…

Computer Science and Game Theory · Computer Science 2012-11-13 Rustam Tagiew

In rational verification, the aim is to verify which temporal logic properties will obtain in a multi-agent system, under the assumption that agents ("players") in the system choose strategies for acting that form a game theoretic…

Computer Science and Game Theory · Computer Science 2023-01-18 Julian Gutierrez , Szymon Kowara , Sarit Kraus , Thomas Steeples , Michael Wooldridge

Escalation is a typical feature of infinite games. Therefore tools conceived for studying infinite mathematical structures, namely those deriving from coinduction are essential. Here we use coinduction, or backward coinduction (to show its…

Computer Science and Game Theory · Computer Science 2010-04-30 Pierre Lescanne , Perrinel Matthieu

Escalation is a typical feature of infinite games. Therefore tools conceived for studying infinite mathematical structures, namely those deriving from coinduction are essential. Here we use coinduction, or backward coinduction (to show its…

Computer Science and Game Theory · Computer Science 2011-12-16 Pierre Lescanne , Perrinel Matthieu

Our paper studies the setting of players using no-regret algorithms in various two-player games. We address whether having stronger regret guarantees or playing against an opponent with weaker regret guarantees yields higher utilities for…

Computer Science and Game Theory · Computer Science 2026-04-29 R. Xu , E. Yachbes , J. Zhang

Online learning in arbitrary, and possibly adversarial, environments has been extensively studied in sequential decision-making, and it is closely connected to equilibrium computation in game theory. Most existing online learning algorithms…

Machine Learning · Computer Science 2026-03-20 Mingyang Liu , Yongshan Chen , Zhiyuan Fan , Gabriele Farina , Asuman Ozdaglar , Kaiqing Zhang

Decent social fairness is highly desired both for socio-economic activities and individuals, as it is one of the cornerstones of our social welfare and sustainability. How to effectively promote the level of fairness thus becomes a…

Physics and Society · Physics 2023-06-27 Guozhong Zheng , Jiqiang Zhang , Zhenwei Ding , Lin Ma , Li Chen

In game theory, mechanism design is concerned with the design of incentives so that a desired outcome of the game can be achieved. In this paper, we study the design of incentives so that a desirable equilibrium is obtained, for instance,…

Computer Science and Game Theory · Computer Science 2021-06-21 Julian Gutierrez , Muhammad Najib , Giuseppe Perelli , Michael Wooldridge

We study two-sided reputational bargaining with opportunities to issue an ultimatum -- threats to force dispute resolution. Each player is either a justified type, who never concedes and issues an ultimatum whenever an opportunity arrives,…

Theoretical Economics · Economics 2021-05-05 Mehmet Ekmekci , Hanzhe Zhang

Evolutionary game theory classically investigates which behavioral patterns are evolutionarily successful in a single game. More recently, a number of contributions have studied the evolution of preferences instead: which subjective…

Computer Science and Game Theory · Computer Science 2015-05-27 Paolo Galeazzi , Michael Franke

We initiate the study of fairness in reinforcement learning, where the actions of a learning algorithm may affect its environment and future rewards. Our fairness constraint requires that an algorithm never prefers one action over another…

Machine Learning · Computer Science 2017-08-08 Shahin Jabbari , Matthew Joseph , Michael Kearns , Jamie Morgenstern , Aaron Roth

The standard game-theoretic solution concept, Nash equilibrium, assumes that all players behave rationally. If we follow a Nash equilibrium and opponents are irrational (or follow strategies from a different Nash equilibrium), then we may…

Computer Science and Game Theory · Computer Science 2023-08-22 Sam Ganzfried

We develop a model to study the role of rationality in economics and biology. The model's agents differ continuously in their ability to make rational choices. The agents' objective is to ensure their individual survival over time or,…

Physics and Society · Physics 2015-07-20 Wolfgang Kuhle

Motivated by cost of computation in game theory, we explore how changing the utilities of players (changing their complexity costs) affects the outcome of a game. We show that even if we improve a player's utility in every action profile,…

Computer Science and Game Theory · Computer Science 2013-12-17 Lior Seeman

This paper studies a variant of two-player zero-sum matrix games, where, at each timestep, the row player selects row $i$, the column player selects column $j$, and the row player receives a noisy reward with expected value $A_{i,j}$, along…

Machine Learning · Computer Science 2025-05-27 Arnab Maiti , Kevin Jamieson , Lillian J. Ratliff

Contextual bandit algorithms have become widely used for recommendation in online systems (e.g. marketplaces, music streaming, news), where they now wield substantial influence on which items get exposed to the users. This raises questions…

Machine Learning · Computer Science 2021-09-14 Lequn Wang , Yiwei Bai , Wen Sun , Thorsten Joachims
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