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Bayesian implementation concerns decision making problems when agents have incomplete information. This paper proposes that the traditional sufficient conditions for Bayesian implementation shall be amended by virtue of a quantum Bayesian…

Data Analysis, Statistics and Probability · Physics 2018-09-24 Haoyang Wu

In stochastic bandit problems, a Bayesian policy called Thompson sampling (TS) has recently attracted much attention for its excellent empirical performance. However, the theoretical analysis of this policy is difficult and its asymptotic…

Statistics Theory · Mathematics 2013-11-11 Junya Honda , Akimichi Takemura

A fundamental problem in science is how to make logical inferences from scientific data. Mere data does not suffice since additional information is necessary to select a domain of models or hypotheses and thus determine the likelihood of…

History and Philosophy of Physics · Physics 2015-06-17 Moorad Alexanian

Consider a Bayesian binary decision-making problem in star networks, where local agents make selfish decisions independently, and a fusion agent makes a final decision based on aggregated decisions and its own private signal. In particular,…

Information Theory · Computer Science 2021-10-27 Daewon Seo , Ravi Kiran Raman , Lav R. Varshney

We propose a truthful-in-expectation, $(1-1/e)$-approximation mechanism for a strategic variant of the generalized assignment problem (GAP). In GAP, a set of items has to be optimally assigned to a set of bins without exceeding the capacity…

Computer Science and Game Theory · Computer Science 2016-08-17 Salman Fadaei , Martin Bichler

We study the problem of finding a small subset of items that is \emph{agreeable} to all agents, meaning that all agents value the subset at least as much as its complement. Previous work has shown worst-case bounds, over all instances with…

Computer Science and Game Theory · Computer Science 2019-02-06 Pasin Manurangsi , Warut Suksompong

We introduce the Funding Game, in which $m$ identical resources are to be allocated among $n$ selfish agents. Each agent requests a number of resources $x_i$ and reports a valuation $\tilde{v}_i(x_i)$, which verifiably {\em lower}-bounds…

Computer Science and Game Theory · Computer Science 2012-11-16 Amotz Bar-Noy , Yi Gai , Matthew P. Johnson , Bhaskar Krishnamachari , George Rabanca

The goal of agents in multi-agent environments is to maximize total reward against the opposing agents that are encountered. Following a game-theoretic solution concept, such as Nash equilibrium, may obtain a strong performance in some…

Computer Science and Game Theory · Computer Science 2026-01-05 Sam Ganzfried

The Bayesian persuasion paradigm of strategic communication models interaction between a privately-informed agent, called the sender, and an ignorant but rational agent, called the receiver. The goal is typically to design a (near-)optimal…

Computer Science and Game Theory · Computer Science 2021-06-21 Ronen Gradwohl , Niklas Hahn , Martin Hoefer , Rann Smorodinsky

A celebrated 1976 theorem of Aumann asserts that honest, rational Bayesian agents with common priors will never "agree to disagree": if their opinions about any topic are common knowledge, then those opinions must be equal. Economists have…

Computational Complexity · Computer Science 2007-05-23 Scott Aaronson

The model of a non-Bayesian agent who faces a repeated game with incomplete information against Nature is an appropriate tool for modeling general agent-environment interactions. In such a model the environment state (controlled by Nature)…

Artificial Intelligence · Computer Science 2014-11-17 D. Monderer , M. Tennenholtz

Bayesian games model interactive decision-making where players have incomplete information -- e.g., regarding payoffs and private data on players' strategies and preferences -- and must actively reason and update their belief models (with…

Computer Science and Game Theory · Computer Science 2024-05-24 Zuyuan Zhang , Mahdi Imani , Tian Lan

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

We study a full implementation problem with a state unknown to the designer but known to agents, where agents have uncertain evidence privately drawn from state-dependent distributions. Stochastic evidence enables ``perfect deceptions,''…

Theoretical Economics · Economics 2025-08-07 Soumen Banerjee , Yi-Chun Chen

We study principal-agent problems in which a principal commits to an outcome-dependent payment scheme (a.k.a. contract) so as to induce an agent to take a costly, unobservable action. We relax the assumption that the principal perfectly…

Computer Science and Game Theory · Computer Science 2021-06-02 Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior…

Computer Science and Game Theory · Computer Science 2015-03-19 Kevin Waugh , Brian D. Ziebart , J. Andrew Bagnell

This paper studies the performative policy learning problem, where agents adjust their features in response to a released policy to improve their potential outcomes, inducing an endogenous distribution shift. There has been growing interest…

Machine Learning · Computer Science 2025-02-25 Qianyi Chen , Ying Chen , Bo Li

Nash equilibria provide a principled framework for modeling interactions in multi-agent decision-making and control. However, many equilibrium-seeking methods implicitly assume that each agent has access to the other agents' objectives and…

Computer Science and Game Theory · Computer Science 2026-03-19 Mahdis Rabbani , Navid Mojahed , Shima Nazari

Game theory has been increasingly applied in settings where the game is not known outright, but has to be estimated by sampling. For example, meta-games that arise in multi-agent evaluation can only be accessed by running a succession of…

Multiagent Systems · Computer Science 2021-01-25 Tabish Rashid , Cheng Zhang , Kamil Ciosek

A version of the classical secretary problem is studied, in which one is interested in selecting one of the b best out of a group of n differently ranked persons who are presented one by one in a random order. It is assumed that b is a…

Probability · Mathematics 2010-09-06 Chris Dietz , Dinard van der Laan , Ad Ridder