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This paper aims to reduce the communication and computation costs of the Nash equilibrium seeking strategy for the $N$-coalition noncooperative games proposed in [1]. The objective is achieved in two manners: 1. An interference graph is…

Optimization and Control · Mathematics 2019-06-05 Maojiao Ye , Guoqiang Hu , Frank L. Lewis , Lihua Xie

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

One of the most complex tasks of decision making and planning is to gather information. This task becomes even more complex when the state is high-dimensional and its belief cannot be expressed with a parametric distribution. Although the…

Artificial Intelligence · Computer Science 2022-09-26 Gilad Rotman , Vadim Indelman

Various planning-based know-how logics have been studied in the recent literature. In this paper, we use such a logic to do know-how-based planning via model checking. In particular, we can handle the higher-order epistemic planning…

Artificial Intelligence · Computer Science 2021-06-23 Yanjun Li , Yanjing Wang

We provide an information-theoretic analysis of Thompson sampling that applies across a broad range of online optimization problems in which a decision-maker must learn from partial feedback. This analysis inherits the simplicity and…

Machine Learning · Computer Science 2015-06-09 Daniel Russo , Benjamin Van Roy

It has long been believed that Chess is the \emph{Drosophila} of Artificial Intelligence (AI). Studying Chess can productively provide valid knowledge about complex systems. Although remarkable progress has been made on solving Chess, the…

Artificial Intelligence · Computer Science 2021-10-25 Ricky Sanjaya , Jun Wang , Yaodong Yang

A mobile agent has to find an inert target in some environment that can be a graph or a terrain in the plane. This task is known as treasure hunt. We consider deterministic algorithms for treasure hunt in trees. Our goal is to establish the…

Data Structures and Algorithms · Computer Science 2025-03-18 Sébastien Bouchard , Arnaud Labourel , Andrzej Pelc

The Fisher information matrix summarizes the amount of information in a set of data relative to the quantities of interest. There are many applications of the information matrix in statistical modeling, system identification and parameter…

Computation · Statistics 2014-05-08 Xumeng Cao

At a mixed Nash equilibrium, the payoff of a player does not depend on her own action, as long as her opponent sticks to his. In a periodic strategy, a concept developed in a previous paper (arXiv:1307.2035v4), in contrast, the own payoff…

Computer Science and Game Theory · Computer Science 2020-05-27 V. K. Oikonomou , J. Jost

We study a simple model of the stochastic information filtering, in a randomly organized information system. For simplest versions of the model it appears to be possible to describe the filtering dynamics in terms of the master equations.…

Disordered Systems and Neural Networks · Physics 2009-11-07 I. S. Manida , Yu. M. Pis'mak

The efficacy of mathematical models heavily depends on the quality of the training data, yet collecting sufficient data is often expensive and challenging. Many modeling applications require inferring parameters only as a means to predict…

The strength of chess engines together with the availability of numerous chess games have attracted the attention of chess players, data scientists, and researchers during the last decades. State-of-the-art engines now provide an…

Artificial Intelligence · Computer Science 2016-07-15 Mathieu Acher , François Esnault

The search task and the system both affect the demand on cognitive resources during information search. In some situations, the demands may become too high for a person. This article has a three-fold goal. First, it presents and critiques…

Human-Computer Interaction · Computer Science 2010-05-18 Jacek Gwizdka

Information retrieval systems such as open web search and recommendation systems are ubiquitous and significantly impact how people receive and consume online information. Previous research has shown the importance of fairness in…

Information Retrieval · Computer Science 2025-03-28 Fumian Chen , Hui Fang

How does competition in markets for information affect the creation and division of surplus? We study this question in a search environment in which an agent searches sequentially for a high-quality good and learns about the quality of…

Theoretical Economics · Economics 2026-05-26 Teddy Mekonnen , Bobak Pakzad-Hurson

We study the two-player safe game of Competitive Diffusion, a game-theoretic model for the diffusion of technologies or influence through a social network. In game theory, safe strategies are mixed strategies with a minimal expected gain…

Discrete Mathematics · Computer Science 2015-07-10 Jeannette Janssen , Celeste Vautour

Information theory has been very successful in obtaining performance limits for various problems such as communication, compression and hypothesis testing. Likewise, stochastic control theory provides a characterization of optimal policies…

Information Theory · Computer Science 2018-10-15 Dhruva Kartik , Ekraam Sabir , Urbashi Mitra , Prem Natarajan

Games, in their mathematical sense, are everywhere (game industries, economics, defense, education, chemistry, biology, ...).Search algorithms in games are artificial intelligence methods for playing such games. Unfortunately, there is no…

Artificial Intelligence · Computer Science 2025-05-16 Quentin Cohen-Solal

This article takes an oblique sidestep from two previous papers, wherein an approach to reformulation of game theory in terms of information theory, topology, as well as a few other notions was indicated. In this document a description is…

Artificial Intelligence · Computer Science 2019-12-03 Christopher Goddard

In this work, we address the challenge of data-efficient exploration in reinforcement learning by examining existing principled, information-theoretic approaches to intrinsic motivation. Specifically, we focus on a class of exploration…

Machine Learning · Computer Science 2025-07-04 Alberto Caron , Chris Hicks , Vasilios Mavroudis