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In probabilistic game structures, probabilistic alternating simulation (PA-simulation) relations preserve formulas defined in probabilistic alternating-time temporal logic with respect to the behaviour of a subset of players. We propose a…

Computer Science and Game Theory · Computer Science 2015-03-19 Chenyi Zhang , Jun Pang

We study the computational complexity of solving stochastic games with mean-payoff objectives. Instead of identifying special classes in which simple strategies are sufficient to play $\epsilon$-optimally, or form $\epsilon$-Nash…

Computer Science and Game Theory · Computer Science 2024-05-16 Sougata Bose , Rasmus Ibsen-Jensen , Patrick Totzke

Two-player stochastic games are games with two 2 players and a randomised entity called "nature". A natural question to ask in this framework is the existence of strategies that ensure that an event happens with probability 1 (almost-sure…

Computer Science and Game Theory · Computer Science 2018-06-27 Youssouf Oualhadj , Léo Tible , Daniele Varacca

In this paper we study continuous-time two-player zero-sum optimal switching games on a finite horizon. Using the theory of doubly reflected BSDEs with interconnected barriers, we show that this game has a value and an equilibrium in the…

Optimization and Control · Mathematics 2018-06-04 Said Hamadène , Randall Martyr , John Moriarty

We introduce a "high probability" framework for repeated games with incomplete information. In our non-equilibrium setting, players aim to guarantee a certain payoff with high probability, rather than in expected value. We provide a high…

Computer Science and Game Theory · Computer Science 2015-09-30 Payam Delgosha , Amin Gohari , Mohammad Akbarpour

Stochastic games are a natural model for the synthesis of controllers confronted to adversarial and/or random actions. In particular, $\omega$-regular games of infinite length can represent reactive systems which are not expected to reach a…

Computer Science and Game Theory · Computer Science 2009-02-17 Florian Horn

A general model for zero-sum stochastic games with asymmetric information is considered. In this model, each player's information at each time can be divided into a common information part and a private information part. Under certain…

Systems and Control · Electrical Eng. & Systems 2019-12-25 Dhruva Kartik , Ashutosh Nayyar

Evolutionary game theory is a powerful mathematical framework to study how intelligent individuals adjust their strategies in collective interactions. It has been widely believed that it is impossible to unilaterally control players'…

Optimization and Control · Mathematics 2021-08-31 Renfei Tan , Qi Su , Bin Wu , Long Wang

Learning problems commonly exhibit an interesting feedback mechanism wherein the population data reacts to competing decision makers' actions. This paper formulates a new game theoretic framework for this phenomenon, called "multi-player…

Computer Science and Game Theory · Computer Science 2022-04-08 Adhyyan Narang , Evan Faulkner , Dmitriy Drusvyatskiy , Maryam Fazel , Lillian J. Ratliff

This paper provides effective methods for the polyhedral formulation of impartial finite combinatorial games as lattice games. Given a rational strategy for a lattice game, a polynomial time algorithm is presented to decide (i) whether a…

Combinatorics · Mathematics 2011-05-30 Alan Guo , Ezra Miller

We provide a self-contained introduction to finite extensive games with perfect information. In these games players proceed in turns having, at each stage, finitely many moves to their disposal, each play always ends, and in each play the…

Computer Science and Game Theory · Computer Science 2022-04-20 Krzysztof R. Apt , Sunil Simon

Nonzero-sum stochastic differential games with impulse controls offer a realistic and far-reaching modelling framework for applications within finance, energy markets, and other areas, but the difficulty in solving such problems has…

Numerical Analysis · Mathematics 2020-06-29 Diego Zabaljauregui

Parity games are abstract infinite-round games that take an important role in formal verification. In the basic setting, these games are two-player, turn-based, and played under perfect information on directed graphs, whose nodes are…

Computer Science and Game Theory · Computer Science 2019-10-31 Antonio Di Stasio , Aniello Murano , Giuseppe Perelli , Moshe Y. Vardi

Markov decision processes (MDPs) provide a standard framework for sequential decision making under uncertainty. However, MDPs do not take uncertainty in transition probabilities into account. Robust Markov decision processes (RMDPs) address…

Artificial Intelligence · Computer Science 2024-05-01 Krishnendu Chatterjee , Ehsan Kafshdar Goharshady , Mehrdad Karrabi , Petr Novotný , Đorđe Žikelić

We investigate the increasingly important and common game-solving setting where we do not have an explicit description of the game but only oracle access to it through gameplay, such as in financial or military simulations and computer…

Artificial Intelligence · Computer Science 2020-02-26 Carlos Martin , Tuomas Sandholm

We consider a two-player zero-sum stochastic differential game in which one of the players has a private information on the game. Both players observe each other, so that the non-informed player can try to guess his missing information. Our…

Probability · Mathematics 2011-06-15 Christine Grün

In two-player finite-state stochastic games of partial observation on graphs, in every state of the graph, the players simultaneously choose an action, and their joint actions determine a probability distribution over the successor states.…

Computer Science and Game Theory · Computer Science 2011-07-13 Krishnendu Chatterjee , Laurent Doyen

We consider discrete time partially observable zero-sum stochastic game with average payoff criterion. We study the game using an equivalent completely observable game. We show that the game has a value and also we come up with a pair of…

Optimization and Control · Mathematics 2014-09-16 Subhamay Saha

We consider 2-player stochastic games with perfectly observed actions, and study the limit, as the discount factor goes to one, of the equilibrium payoffs set. In the usual setup where current states are observed by the players, we show…

Optimization and Control · Mathematics 2014-12-11 Jérôme Renault , Bruno Ziliotto

We investigate the problem of gambling with uncertainty in outcome probabilities. Stochastic optimization models are proposed for optimal investing on events with mutually exclusive outcomes when probabilities are estimated using…

Optimization and Control · Mathematics 2017-08-03 Michael R. Metel
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