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Approximating the Value of Energy-Parity Objectives in Simple Stochastic Games

Authors Mohan Dantam, Richard Mayr

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Mohan Dantam
  • School of Informatics, University of Edinburgh, UK
Richard Mayr
  • School of Informatics, University of Edinburgh, UK

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Mohan Dantam and Richard Mayr. Approximating the Value of Energy-Parity Objectives in Simple Stochastic Games. In 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 272, pp. 38:1-38:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.MFCS.2023.38

Abstract

We consider simple stochastic games 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 parity condition.
We present an algorithm to approximate the value of a given configuration in 2-NEXPTIME. Moreover, ε-optimal strategies for either player require at most O(2-EXP(|G|)⋅log(1/ε)) memory modes.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Stochastic games
Keywords
  • Energy-Parity Games
  • Simple Stochastic Games
  • Parity
  • Energy

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