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We study zero-sum differential games with state constraints and one-sided information, where the informed player (Player 1) has a categorical payoff type unknown to the uninformed player (Player 2). The goal of Player 1 is to minimize his…

Computer Science and Game Theory · Computer Science 2024-06-05 Mukesh Ghimire , Lei Zhang , Zhe Xu , Yi Ren

This work considers two-player zero-sum semi-Markov games with incomplete information on one side and perfect observation. At the beginning, the system selects a game type according to a given probability distribution and informs to Player…

Optimization and Control · Mathematics 2021-07-16 Fang Chen , Xianping Guo , Zhong-Wei Liao

This paper provides sufficient conditions for the existence of solutions for two-person zero-sum games with inf/sup-compact payoff functions and with possibly noncompact decision sets for both players. Payoff functions may be unbounded, and…

Optimization and Control · Mathematics 2021-12-22 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

Information uncertainty is one of the major challenges facing applications of game theory. In the context of Stackelberg games, various approaches have been proposed to deal with the leader's incomplete knowledge about the follower's…

Computer Science and Game Theory · Computer Science 2019-05-21 Jiarui Gan , Haifeng Xu , Qingyu Guo , Long Tran-Thanh , Zinovi Rabinovich , Michael Wooldridge

Motivated by emerging decentralized applications, the \emph{game of coding} framework has been recently introduced to address scenarios where the adversary's control over coded symbols surpasses the fundamental limits of traditional coding…

Information Theory · Computer Science 2025-02-12 Hanzaleh Akbarinodehi , Parsa Moradi , Mohammad Ali Maddah-Ali

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid…

Systems and Control · Electrical Eng. & Systems 2024-10-22 Adam Lechowicz , Joshua Comden , Andrey Bernstein

The maximization of submodular functions is an NP-Hard problem for certain subclasses of functions, for which a simple greedy algorithm has been shown to guarantee a solution whose quality is within 1/2 of the optimal. When this algorithm…

Data Structures and Algorithms · Computer Science 2019-01-11 David Grimsman , Mohd. Shabbir Ali , João P. Hespanha , Jason R. Marden

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

Best-response mechanisms (Nisan, Schapira, Valiant, Zohar, 2011) provide a unifying framework for studying various distributed protocols in which the participants are instructed to repeatedly best respond to each others' strategies. Two…

Computer Science and Game Theory · Computer Science 2014-02-03 Diodato Ferraioli , Paolo Penna

Networked public goods games model scenarios in which self-interested agents decide whether or how much to invest in an action that benefits not only themselves, but also their network neighbors. Examples include vaccination, security…

Computer Science and Game Theory · Computer Science 2021-09-03 David Kempe , Sixie Yu , Yevgeniy Vorobeychik

The game-theoretic risk management framework put forth in the precursor work "Towards a Theory of Games with Payoffs that are Probability-Distributions" (arXiv:1506.07368 [q-fin.EC]) is herein extended by algorithmic details on how to…

General Economics · Economics 2020-04-10 Stefan Rass

Stochastic two-player games model systems with an environment that is both adversarial and stochastic. The adversarial part of the environment is modeled by a player (Player 2) who tries to prevent the system (Player 1) from achieving its…

Computer Science and Game Theory · Computer Science 2025-06-11 Laurent Doyen , Pranshu Gaba , Shibashis Guha

We design and analyze minimax-optimal algorithms for online linear optimization games where the player's choice is unconstrained. The player strives to minimize regret, the difference between his loss and the loss of a post-hoc benchmark…

Machine Learning · Computer Science 2013-02-12 H. Brendan McMahan

We extend the optimin notion of Ismail (2025) from mixed strategy profiles to correlated distributions. A correlated distribution is evaluated by the worst expected payoff each player can receive when opponents may either obey their private…

Theoretical Economics · Economics 2026-05-20 Mehmet Mars Seven

Partial monitoring is an expressive framework for sequential decision-making with an abundance of applications, including graph-structured and dueling bandits, dynamic pricing and transductive feedback models. We survey and extend recent…

Machine Learning · Computer Science 2023-11-15 Johannes Kirschner , Tor Lattimore , Andreas Krause

It is well-known that acting in an individually rational manner, according to the principles of classical game theory, may lead to sub-optimal solutions in a class of problems named social dilemmas. In contrast, humans generally do not have…

Computer Science and Game Theory · Computer Science 2014-01-16 Steven de Jong , Simon Uyttendaele , Karl Tuyls

In this paper we formulate the fixed budget resource allocation game to understand the performance of a distributed market-based resource allocation system. Multiple users decide how to distribute their budget (bids) among multiple machines…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Michal Feldman , Kevin Lai , Li Zhang

We study information design settings where the designer controls information about a state, and there are multiple agents interacting in a game who are privately informed about their types. Each agent's utility depends on all agents' types…

Theoretical Economics · Economics 2022-01-31 Ozan Candogan , Philipp Strack

Given a batch of human computation tasks, a commonly ignored aspect is how the price (i.e., the reward paid to human workers) of these tasks must be set or varied in order to meet latency or cost constraints. Often, the price is set…

Computer Science and Game Theory · Computer Science 2014-08-28 Yihan Gao , Aditya Parameswaran

Decision making under uncertainty is at the heart of any autonomous system acting with imperfect information. The cost of solving the decision making problem is exponential in the action and observation spaces, thus rendering it unfeasible…

Artificial Intelligence · Computer Science 2024-06-18 Tom Yotam , Vadim Indelman
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