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Most algorithmic studies on multi-agent information design so far have focused on the restricted situation with no inter-agent externalities; a few exceptions investigated truly strategic games such as zero-sum games and second-price…

Computer Science and Game Theory · Computer Science 2022-09-07 Chenghan Zhou , Thanh H. Nguyen , Haifeng Xu

We study a fair division problem with indivisible items, namely the computation of maximin share allocations. Given a set of $n$ players, the maximin share of a single player is the best she can guarantee to herself, if she would partition…

Computer Science and Game Theory · Computer Science 2016-05-16 Georgios Amanatidis , Georgios Birmpas , Evangelos Markakis

Communication is rarely perfect, but rather prone to error of transmission and reception. Often the origin of these errors cannot be properly quantified and is thus imprecisely known. We analyze the impact of an ambiguous noise which may…

Theoretical Economics · Economics 2023-11-22 Gerrit Bauch

There is a long history in game theory on the topic of Bayesian or "rational" learning, in which each player maintains beliefs over a set of alternative behaviours, or types, for the other players. This idea has gained increasing interest…

Artificial Intelligence · Computer Science 2016-03-03 Stefano V. Albrecht , Jacob W. Crandall , Subramanian Ramamoorthy

We address the brittleness of Bayesian experimental design under model misspecification by formulating the problem as a max--min game between the experimenter and an adversarial nature subject to information-theoretic constraints. We…

Machine Learning · Statistics 2026-05-13 Hany Abdulsamad , Sahel Iqbal , Christian A. Naesseth , Takuo Matsubara , Adrien Corenflos

In this paper we investigate lossy channel games under incomplete information, where two players operate on a finite set of unbounded FIFO channels and one player, representing a system component under consideration operates under…

Logic in Computer Science · Computer Science 2013-03-05 Rayna Dimitrova , Bernd Finkbeiner

The combination of the Bayesian game and learning has a rich history, with the idea of controlling a single agent in a system composed of multiple agents with unknown behaviors given a set of types, each specifying a possible behavior for…

Machine Learning · Computer Science 2024-11-21 Tongxin Li , Tinashe Handina , Shaolei Ren , Adam Wierman

There has been a recent surge of interest in the role of information in strategic interactions. Much of this work seeks to understand how the realized equilibrium of a game is influenced by uncertainty in the environment and the information…

Computer Science and Game Theory · Computer Science 2014-07-22 Shaddin Dughmi

We address the online linear optimization problem when the actions of the forecaster are represented by binary vectors. Our goal is to understand the magnitude of the minimax regret for the worst possible set of actions. We study the…

Machine Learning · Statistics 2011-05-25 Jean-Yves Audibert , Sebastien Bubeck , Gabor Lugosi

Min-max optimization problems (i.e., min-max games) have been attracting a great deal of attention because of their applicability to a wide range of machine learning problems. Although significant progress has been made recently, the…

Computer Science and Game Theory · Computer Science 2023-07-07 Denizalp Goktas , Amy Greenwald

Secure equilibrium is a refinement of Nash equilibrium, which provides some security to the players against deviations when a player changes his strategy to another best response strategy. The concept of secure equilibrium is specifically…

Computer Science and Game Theory · Computer Science 2014-05-08 Julie De Pril , János Flesch , Jeroen Kuipers , Gijs Schoenmakers , Koos Vrieze

The strategic selection of resources by selfish agents is a classic research direction, with Resource Selection Games and Congestion Games as prominent examples. In these games, agents select available resources and their utility then…

Computer Science and Game Theory · Computer Science 2024-06-14 Jonathan Gadea Harder , Simon Krogmann , Pascal Lenzner , Alexander Skopalik

This article introduces a framework for evaluating statistical decisions under both prior ambiguity and likelihood misspecification. We begin with an ambiguity set - a frequentist model that pairs a possibly misspecified likelihood with…

Econometrics · Economics 2026-05-14 Karun Adusumilli

Concurrent multi-player games with $\omega$-regular objectives are a standard model for systems that consist of several interacting components, each with its own objective. The standard solution concept for such games is Nash Equilibrium,…

Computer Science and Game Theory · Computer Science 2022-09-28 Shaull Almagor , Shai Guendelman

We study nondeterministic strategies in parity games with the aim of computing a most permissive winning strategy. Following earlier work, we measure permissiveness in terms of the average number/weight of transitions blocked by the…

Logic in Computer Science · Computer Science 2013-01-14 Patricia Bouyer , Nicolas Markey , Jörg Olschewski , Michael Ummels

We study a class of deterministic mean field games on finite and infinite time horizons arising in models of optimal exploitation of exhaustible resources. The main characteristic of our game is an absorption constraint on the players'…

General Economics · Economics 2021-04-14 Paulwin Graewe , Ulrich Horst , Ronnie Sircar

Deception is a technique to mislead human or computer systems by manipulating beliefs and information. Successful deception is characterized by the information-asymmetric, dynamic, and strategic behaviors of the deceiver and the deceivee.…

Cryptography and Security · Computer Science 2018-10-02 Tao Zhang , Quanyan zhu

Currently the Dempster-Shafer based algorithm and Uniform Random Probability based algorithm are the preferred method of resolving security games, in which defenders are able to identify attackers and only strategy remained ambiguous.…

Artificial Intelligence · Computer Science 2015-08-11 Hossein Khani , Mohsen Afsharchi

Modeling the interaction between traffic agents is a key issue in designing safe and non-conservative maneuvers in autonomous driving. This problem can be challenging when multi-modality and behavioral uncertainties are engaged. Existing…

Robotics · Computer Science 2024-09-24 Zhenmin Huang , Tong Li , Shaojie Shen , Jun Ma

The existence of a phase transition with diverging susceptibility in batch Minority Games (MGs) is the mark of informationally efficient regimes and is linked to the specifics of the agents' learning rules. Here we study how the standard…

Physics and Society · Physics 2009-11-13 Tobias Galla , Andrea De Martino