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Related papers: Blackwell Approachability and Minimax Theory

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Computing reachability probabilities is a fundamental problem in the analysis of probabilistic programs. This paper aims at a comprehensive and comparative account on various martingale-based methods for over- and under-approximating…

Programming Languages · Computer Science 2018-11-16 Toru Takisaka , Yuichiro Oyabu , Natsuki Urabe , Ichiro Hasuo

We study the complexity of deciding the existence of mixed equilibria for minimization games where players use valuations other than expectation to evaluate their costs. We consider risk-averse players seeking to minimize the sum…

Computer Science and Game Theory · Computer Science 2015-11-02 Marios Mavronicolas , Burkhard Monien

We study a class of stochastic dynamic games that exhibit strategic complementarities between players; formally, in the games we consider, the payoff of a player has increasing differences between her own state and the empirical…

Computer Science and Game Theory · Computer Science 2010-12-13 Sachin Adlakha , Ramesh Johari

Classical reactive synthesis approaches aim to synthesize a reactive system that always satisfies a given specifications. These approaches often reduce to playing a two-player zero-sum game where the goal is to synthesize a winning…

Computer Science and Game Theory · Computer Science 2025-06-09 Karan Muvvala , Qi Heng Ho , Morteza Lahijanian

Reachability analysis is an important method in providing safety guarantees for systems with unknown or uncertain dynamics. Due to the computational intractability of exact reachability analysis for general nonlinear, high-dimensional…

Systems and Control · Electrical Eng. & Systems 2025-09-12 Elizabeth Dietrich , Rosalyn Devonport , Stephen Tu , Murat Arcak

A general formulation of the basic conflict of the information problem is given, encapsulated in a "black hole theorem." This is framed in a more general context than the usual one of quantum field theory on a background, and is based on…

High Energy Physics - Theory · Physics 2023-02-27 Steven B. Giddings

Partially observable stochastic games provide a rich mathematical paradigm for modeling multi-agent dynamic decision making under uncertainty and partial information. However, they generally do not admit closed-form solutions and are…

Optimization and Control · Mathematics 2020-04-15 Yanling Chang , Chelsea C. White

We study a game where one player selects a random function, and the other has to guess that function, and show that with high probability the second player can correctly guess most of the random function. We apply this analysis to…

Optimization and Control · Mathematics 2023-11-28 Catherine Rainer , Eilon Solan

We consider the decidability of state-to-state reachability in linear time-invariant control systems over discrete time. We analyse this problem with respect to the allowable control sets, which in general are assumed to be defined by…

Optimization and Control · Mathematics 2020-11-19 Nathanaël Fijalkow , Joël Ouaknine , Amaury Pouly , João Sousa-Pinto , James Worrell

We investigate a two-player zero-sum stochastic differential game in which one of the players has more information on the game than his opponent. We show how to construct numerical schemes for the value function of this game, which is given…

Computer Science and Game Theory · Computer Science 2011-11-18 Christine Grün

This paper presents a new proof of the renewal theorem by bijecting a general point process to a deterministic one (where the time between events is always fixed). It also provides insight into the workings of the renewal theorem.

Probability · Mathematics 2021-08-03 Rohit Pandey

Many important values for cooperative games are known to arise from least square optimization problems. The present investigation develops an optimization framework to explain and clarify this phenomenon in a general setting. The main…

Optimization and Control · Mathematics 2016-01-13 Ulrich Faigle , Michel Grabisch

We introduce Bayesimax theory, a paradigm for objective Bayesian analysis which selects priors by applying minimax theory to prior disclosure games. In these games, the uniquely optimal strategy for a Bayesian agent upon observing the data…

Statistics Theory · Mathematics 2025-09-09 Sitaram Vangala

As real-world images come in varying sizes, the machine learning model is part of a larger system that includes an upstream image scaling algorithm. In this paper, we investigate the interplay between vulnerabilities of the image scaling…

Machine Learning · Computer Science 2022-06-22 Yue Gao , Ilia Shumailov , Kassem Fawaz

We consider games played on the transtion graph of concurrent programs running under the Total Store Order (TSO) weak memory model. Games are frequently used to model the interaction between a system and its environment, in this case…

Computer Science and Game Theory · Computer Science 2024-06-05 Stephan Spengler

Imitation is simple behavior which uses successful actions of others in order to deal with one's own problems. Because success of imitation generally depends on whether profit of an imitating agent coincides with those of other agents or…

Physics and Society · Physics 2023-01-23 Masahiko Ueda

We consider how an agent should update her beliefs when her beliefs are represented by a set P of probability distributions, given that the agent makes decisions using the minimax criterion, perhaps the best-studied and most commonly-used…

Artificial Intelligence · Computer Science 2014-01-17 Peter D Grunwald , Joseph Y Halpern

We consider the safety evaluation of discrete time, stochastic systems over a finite horizon. Therefore, we discuss and link probabilistic invariance with reachability as well as reach-avoid problems. We show how to efficiently compute…

Systems and Control · Electrical Eng. & Systems 2023-04-17 Niklas Schmid , John Lygeros

This paper deals with a standard stochastic game model with a continuum of states under the duel-type setup. It newly proposes a hybrid model of game theory and the fluctuation process, which could be applied for various practical decision…

Optimization and Control · Mathematics 2020-08-10 Song-Kyoo Kim

We study a two-player, zero-sum, stochastic game with incomplete information on one side in which the players are allowed to play more and more frequently. The informed player observes the realization of a Markov chain on which the payoffs…

Optimization and Control · Mathematics 2013-07-15 Pierre Cardaliaguet , Catherine Rainer , Dinah Rosenberg , Nicolas Vieille
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