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We prove a new minimax theorem connecting the worst-case Bayesian regret and minimax regret under partial monitoring with no assumptions on the space of signals or decisions of the adversary. We then generalise the information-theoretic…

Machine Learning · Computer Science 2019-05-30 Tor Lattimore , Csaba Szepesvari

We consider a selfish variant of the knapsack problem. In our version, the items are owned by agents, and each agent can misrepresent the set of items she owns---either by avoiding reporting some of them (understating), or by reporting…

Computer Science and Game Theory · Computer Science 2016-03-01 Itai Feigenbaum , Matthew P. Johnson

We study the problem of designing replication-proof bandit mechanisms when agents strategically register or replicate their own arms to maximize their payoff. Specifically, we consider Bayesian agents who only know the distribution from…

Computer Science and Game Theory · Computer Science 2025-02-04 Suho Shin , Seyed A. Esmaeili , MohammadTaghi Hajiaghayi

The problem of estimating event truths from conflicting agent opinions in a social network is investigated. An autoencoder learns the complex relationships between event truths, agent reliabilities and agent observations. A Bayesian network…

Machine Learning · Computer Science 2021-01-26 Jielong Yang , Wee Peng Tay

In this work, we consider the consensus problem in which legitimate agents share their values over an undirected communication network in the presence of malicious or faulty agents. Different from the previous works, we characterize the…

Systems and Control · Electrical Eng. & Systems 2024-03-27 Sarper Aydın , Orhan Eren Akgün , Stephanie Gil , Angelia Nedić

We address Nash equilibrium problems in a partial-decision information scenario, where each agent can only exchange information with some neighbors, while its cost function possibly depends on the strategies of all agents. We characterize…

Optimization and Control · Mathematics 2022-06-24 Mattia Bianchi , Sergio Grammatico

We consider a variant of continuous-state partially-observable stochastic games with neural perception mechanisms and an asymmetric information structure. One agent has partial information, with the observation function implemented as a…

Computer Science and Game Theory · Computer Science 2024-04-17 Rui Yan , Gabriel Santos , Gethin Norman , David Parker , Marta Kwiatkowska

Until now, distributed algorithms for rational agents have assumed a-priori knowledge of $n$, the size of the network. This assumption is challenged here by proving how much a-priori knowledge is necessary for equilibrium in different…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-16 Yehuda Afek , Yishay Mansour , Shaked Rafaeli , Moshe Sulamy

When multiple informative equilibria are possible in a general cheap talk game, how much information can a principal guarantee herself? To answer this question, I define the notion of worst-case implementation-implementation via the worst…

Theoretical Economics · Economics 2026-02-17 Andrei Iakovlev

The literature on strategic communication originated with the influential cheap talk model, which precedes the Bayesian persuasion model by three decades. This model describes an interaction between two agents: sender and receiver. The…

Computer Science and Game Theory · Computer Science 2024-09-11 Yakov Babichenko , Inbal Talgam-Cohen , Haifeng Xu , Konstantin Zabarnyi

We consider an example of stochastic games with partial, asymmetric and non-classical information. We obtain relevant equilibrium policies using a new approach which allows managing the belief updates in a structured manner. Agents have…

Computer Science and Game Theory · Computer Science 2019-09-17 Veeraruna Kavitha , Mayank Maheshwari , Eitan Altman

Recently, there has been a number of papers relating mechanism design and privacy (e.g., see \cite{MT07,Xia11,CCKMV11,NST12,NOS12,HK12}). All of these papers consider a worst-case setting where there is no probabilistic information about…

Computer Science and Game Theory · Computer Science 2014-11-25 Samantha Leung , Edward Lui

In traditional mechanism design, agents only care about the utility they derive from the outcome of the mechanism. We look at a richer model where agents also assign non-negative dis-utility to the information about their private types…

Computer Science and Game Theory · Computer Science 2015-03-19 Kobbi Nissim , Claudio Orlandi , Rann Smorodinsky

Typically, when evaluating Theory of Mind, we consider the beliefs of others to be binary: held or not held. But what if someone is unsure about their own beliefs? How can we quantify this uncertainty? We propose a new suite of tasks,…

Computation and Language · Computer Science 2024-09-24 Anthony Sicilia , Malihe Alikhani

The contextual bandit problem, where agents arrive sequentially with personal contexts and the system adapts its arm allocation decisions accordingly, has recently garnered increasing attention for enabling more personalized outcomes.…

Machine Learning · Computer Science 2025-05-06 Yiting Hu , Lingjie Duan

Enterprise agents increasingly operate inside scoped retrieval systems, delegated workflows, and policy-constrained evidence environments. In these settings, access control can be enforced correctly while the system still produces an answer…

Artificial Intelligence · Computer Science 2026-05-08 Krti Tallam

We introduce a general approach based on \emph{selective verification} and obtain approximate mechanisms without money for maximizing the social welfare in the general domain of utilitarian voting. Having a good allocation in mind, a…

Computer Science and Game Theory · Computer Science 2015-07-10 Dimitris Fotakis , Christos Tzamos , Emmanouil Zampetakis

This paper concerns sequential hypothesis testing in competitive multi-agent systems where agents exchange potentially manipulated information. Specifically, a two-agent scenario is studied where each agent aims to correctly infer the true…

Systems and Control · Electrical Eng. & Systems 2025-04-04 Aneesh Raghavan , M. Umar B. Niazi , Karl H. Johansson

Distributed aggregative optimization methods are gaining increased traction due to their ability to address cooperative control and optimization problems, where the objective function of each agent depends not only on its own decision…

Multiagent Systems · Computer Science 2025-06-03 Ziqin Chen , Magnus Egerstedt , Yongqiang Wang

It is typically expected that if a mechanism is truthful, then the agents would, indeed, truthfully report their private information. But why would an agent believe that the mechanism is truthful? We wish to design truthful mechanisms,…

Computer Science and Game Theory · Computer Science 2014-12-02 Simina Brânzei , Ariel D. Procaccia
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