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Documents authored by Dantam, Mohan

Document
Track B: Automata, Logic, Semantics, and Theory of Programming
DOI: 10.4230/LIPIcs.ICALP.2024.133
Finite-Memory Strategies for Almost-Sure Energy-MeanPayoff Objectives in MDPs

Authors: Mohan Dantam and Richard Mayr

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)

Abstract
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 show that finite memory suffices for almost surely winning strategies for the Energy-MeanPayoff objective. This is in contrast to the closely related Energy-Parity objective, where almost surely winning strategies require infinite memory in general. We show that exponential memory is sufficient (even for deterministic strategies) and necessary (even for randomized strategies) for almost surely winning Energy-MeanPayoff. The upper bound holds even if the strictly positive mean payoff part of the objective is generalized to multidimensional strictly positive mean payoff. Finally, it is decidable in pseudo-polynomial time whether an almost surely winning strategy exists.
Cite as

Mohan Dantam and Richard Mayr. Finite-Memory Strategies for Almost-Sure Energy-MeanPayoff Objectives in MDPs. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 133:1-133:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{dantam_et_al:LIPIcs.ICALP.2024.133,
  author =	{Dantam, Mohan and Mayr, Richard},
  title =	{{Finite-Memory Strategies for Almost-Sure Energy-MeanPayoff Objectives in MDPs}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{133:1--133:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.133},
  URN =		{urn:nbn:de:0030-drops-202762},
  doi =		{10.4230/LIPIcs.ICALP.2024.133},
  annote =	{Keywords: Markov decision processes, energy, mean payoff, parity, strategy complexity}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2023.38
Approximating the Value of Energy-Parity Objectives in Simple Stochastic Games

Authors: Mohan Dantam and Richard Mayr

Published in: LIPIcs, Volume 272, 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023)

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.
Cite as

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)

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@InProceedings{dantam_et_al:LIPIcs.MFCS.2023.38,
  author =	{Dantam, Mohan and Mayr, Richard},
  title =	{{Approximating the Value of Energy-Parity Objectives in Simple Stochastic Games}},
  booktitle =	{48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023)},
  pages =	{38:1--38:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-292-1},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{272},
  editor =	{Leroux, J\'{e}r\^{o}me and Lombardy, Sylvain and Peleg, David},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2023.38},
  URN =		{urn:nbn:de:0030-drops-185724},
  doi =		{10.4230/LIPIcs.MFCS.2023.38},
  annote =	{Keywords: Energy-Parity Games, Simple Stochastic Games, Parity, Energy}
}
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