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In this work we offer an $O(|V|^2 |E|\, W)$ pseudo-polynomial time deterministic algorithm for solving the Value Problem and Optimal Strategy Synthesis in Mean Payoff Games. This improves by a factor $\log(|V|\, W)$ the best previously…

Data Structures and Algorithms · Computer Science 2016-04-26 Carlo Comin , Romeo Rizzi

This note studies structural aspects concerning Optimal Positional Strategies (OPSs) in Mean Payoff Games (MPGs), it is a contribution to understanding the relationship between OPSs in MPGs and Small Energy-Progress Measures (SEPMs) in…

Computer Science and Game Theory · Computer Science 2016-12-05 Carlo Comin

Graph games provide the foundation for modeling and synthesis of reactive processes. Such games are played over graphs where the vertices are controlled by two adversarial players. We consider graph games where the objective of the first…

Computer Science and Game Theory · Computer Science 2017-06-21 Krishnendu Chatterjee , Monika Henzinger , Alexander Svozil

An improved exponential time algorithm for Energy Games and Mean Payoff Games has been recently proposed in ICALP 19. The new algorithm prevents some of the repetitive operations performed by the classic value iteration algorithm of Brim et…

Data Structures and Algorithms · Computer Science 2023-10-09 Peter Austin , Daniele Dell'Erba

We design a novel algorithm for solving Mean-Payoff Games (MPGs). Besides solving an MPG in the usual sense, our algorithm computes more information about the game, information that is important with respect to applications. The weights of…

Computer Science and Game Theory · Computer Science 2010-06-09 Luboš Brim , Jakub Chaloupka

In a mean-payoff parity game, one of the two players aims both to achieve a qualitative parity objective and to minimize a quantitative long-term average of payoffs (aka. mean payoff). The game is zero-sum and hence the aim of the other…

Computer Science and Game Theory · Computer Science 2020-01-15 Laure Daviaud , Marcin Jurdzinski , Ranko Lazic

We generalise the hyperplane separation technique (Chatterjee and Velner, 2013) from multi-dimensional mean-payoff to energy games, and achieve an algorithm for solving the latter whose running time is exponential only in the dimension, but…

Computer Science and Game Theory · Computer Science 2021-09-07 Marcin Jurdziński , Ranko Lazić , Sylvain Schmitz

Energy games belong to a class of turn-based two-player infinite-duration games}played on a weighted directed graph. It is one of the rare and intriguing combinatorial problems that lie in ${\sf NP} \cap {\sf co\mbox{-}NP}$, but are not…

Data Structures and Algorithms · Computer Science 2018-03-02 Krishnendu Chatterjee , Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

Multi-dimensional mean-payoff and energy games provide the mathematical foundation for the quantitative study of reactive systems, and play a central role in the emerging quantitative theory of verification and synthesis. In this work, we…

Computer Science and Game Theory · Computer Science 2014-11-04 Krishnendu Chatterjee , Mickael Randour , Jean-François Raskin

We develop value iteration-based algorithms to solve in a unified manner different classes of combinatorial zero-sum games with mean-payoff type rewards. These algorithms rely on an oracle, evaluating the dynamic programming operator up to…

Computer Science and Game Theory · Computer Science 2024-11-12 Xavier Allamigeon , Stéphane Gaubert , Ricardo D. Katz , Mateusz Skomra

Energy parity games are infinite two-player turn-based games played on weighted graphs. The objective of the game combines a (qualitative) parity condition with the (quantitative) requirement that the sum of the weights (i.e., the level of…

Logic in Computer Science · Computer Science 2012-04-04 Krishnendu Chatterjee , Laurent Doyen

We study the algorithm of Gurvich, Khachyian and Karzanov (GKK algorithm) when it is ran over mean-payoff games with no simple cycle of weight zero. We propose a new symmetric analysis, lowering the $O(n^2 N)$ upper-bound of Pisaruk on the…

Computer Science and Game Theory · Computer Science 2021-10-12 Pierre Ohlmann

In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always…

Computer Science and Game Theory · Computer Science 2012-09-17 Yaron Velner , Krishnendu Chatterjee , Laurent Doyen , Thomas A. Henzinger , Alexander Rabinovich , Jean-Francois Raskin

Quantitative games, where quantitative objectives are defined on weighted game arenas, provide natural tools for designing faithful models of embedded controllers. Instances of these games that recently gained interest are the so called…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-10-11 Andrea Formisano , Raffaella Gentilini , Flavio Vella

Quantitative games are two-player zero-sum games played on directed weighted graphs. Total-payoff games (that can be seen as a refinement of the well-studied mean-payoff games) are the variant where the payoff of a play is computed as the…

Computer Science and Game Theory · Computer Science 2015-07-15 Thomas Brihaye , Gilles Geeraerts , Axel Haddad , Benjamin Monmege

Often one has a preference order among the different systems that satisfy a given specification. Under a probabilistic assumption about the possible inputs, such a preference order is naturally expressed by a weighted automaton, which…

Logic in Computer Science · Computer Science 2011-04-15 Krishnendu Chatterjee , Thomas A. Henzinger , Barbara Jobstmann , Rohit Singh

We consider two-person zero-sum stochastic mean payoff games with perfect information, or BWR-games, given by a digraph $G = (V, E)$, with local rewards $r: E \to \ZZ$, and three types of positions: black $V_B$, white $V_W$, and random…

Computer Science and Game Theory · Computer Science 2017-03-27 Endre Boros , Khaled Elbassioni , Vladimir Gurvich , Kazuhisa Makino

We consider simple stochastic games $\mathcal G$ with energy-parity objectives, a combination of quantitative rewards with a qualitative parity condition. The Maximizer tries to avoid running out of energy while simultaneously satisfying a…

Computer Science and Game Theory · Computer Science 2023-07-13 Mohan Dantam , Richard Mayr

We consider finite-state Markov decision processes with the combined Energy-MeanPayoff objective. The controller tries to avoid running out of energy while simultaneously attaining a strictly positive mean payoff in a second dimension. We…

Computer Science and Game Theory · Computer Science 2025-10-13 Mohan Dantam , Richard Mayr

We revisit the problem of finding optimal strategies for deterministic Markov Decision Processes (DMDPs), and a closely related problem of testing feasibility of systems of $m$ linear inequalities on $n$ real variables with at most two…

Data Structures and Algorithms · Computer Science 2021-10-29 Adam Karczmarz
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