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Documents authored by Parreaux, Julie


Document
Decidability of One-Clock Weighted Timed Games with Arbitrary Weights

Authors: Benjamin Monmege, Julie Parreaux, and Pierre-Alain Reynier

Published in: LIPIcs, Volume 243, 33rd International Conference on Concurrency Theory (CONCUR 2022)


Abstract
Weighted Timed Games (WTG for short) are the most widely used model to describe controller synthesis problems involving real-time issues. Unfortunately, they are notoriously difficult, and undecidable in general. As a consequence, one-clock WTG has attracted a lot of attention, especially because they are known to be decidable when only non-negative weights are allowed. However, when arbitrary weights are considered, despite several recent works, their decidability status was still unknown. In this paper, we solve this problem positively and show that the value function can be computed in exponential time (if weights are encoded in unary).

Cite as

Benjamin Monmege, Julie Parreaux, and Pierre-Alain Reynier. Decidability of One-Clock Weighted Timed Games with Arbitrary Weights. In 33rd International Conference on Concurrency Theory (CONCUR 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 243, pp. 15:1-15:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{monmege_et_al:LIPIcs.CONCUR.2022.15,
  author =	{Monmege, Benjamin and Parreaux, Julie and Reynier, Pierre-Alain},
  title =	{{Decidability of One-Clock Weighted Timed Games with Arbitrary Weights}},
  booktitle =	{33rd International Conference on Concurrency Theory (CONCUR 2022)},
  pages =	{15:1--15:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-246-4},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{243},
  editor =	{Klin, Bartek and Lasota, S{\l}awomir and Muscholl, Anca},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2022.15},
  URN =		{urn:nbn:de:0030-drops-170786},
  doi =		{10.4230/LIPIcs.CONCUR.2022.15},
  annote =	{Keywords: Weighted timed games, Algorithmic game theory, Timed automata}
}
Document
Track B: Automata, Logic, Semantics, and Theory of Programming
Playing Stochastically in Weighted Timed Games to Emulate Memory

Authors: Benjamin Monmege, Julie Parreaux, and Pierre-Alain Reynier

Published in: LIPIcs, Volume 198, 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021)


Abstract
Weighted timed games are two-player zero-sum games played in a timed automaton equipped with integer weights. We consider optimal reachability objectives, in which one of the players, that we call Min, wants to reach a target location while minimising the cumulated weight. While knowing if Min has a strategy to guarantee a value lower than a given threshold is known to be undecidable (with two or more clocks), several conditions, one of them being the divergence, have been given to recover decidability. In such weighted timed games (like in untimed weighted games in the presence of negative weights), Min may need finite memory to play (close to) optimally. This is thus tempting to try to emulate this finite memory with other strategic capabilities. In this work, we allow the players to use stochastic decisions, both in the choice of transitions and of timing delays. We give for the first time a definition of the expected value in weighted timed games, overcoming several theoretical challenges. We then show that, in divergent weighted timed games, the stochastic value is indeed equal to the classical (deterministic) value, thus proving that Min can guarantee the same value while only using stochastic choices, and no memory.

Cite as

Benjamin Monmege, Julie Parreaux, and Pierre-Alain Reynier. Playing Stochastically in Weighted Timed Games to Emulate Memory. In 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 198, pp. 137:1-137:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{monmege_et_al:LIPIcs.ICALP.2021.137,
  author =	{Monmege, Benjamin and Parreaux, Julie and Reynier, Pierre-Alain},
  title =	{{Playing Stochastically in Weighted Timed Games to Emulate Memory}},
  booktitle =	{48th International Colloquium on Automata, Languages, and Programming (ICALP 2021)},
  pages =	{137:1--137:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-195-5},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{198},
  editor =	{Bansal, Nikhil and Merelli, Emanuela and Worrell, James},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2021.137},
  URN =		{urn:nbn:de:0030-drops-142066},
  doi =		{10.4230/LIPIcs.ICALP.2021.137},
  annote =	{Keywords: Weighted timed games, Algorithmic game theory, Randomisation}
}
Document
Reaching Your Goal Optimally by Playing at Random with No Memory

Authors: Benjamin Monmege, Julie Parreaux, and Pierre-Alain Reynier

Published in: LIPIcs, Volume 171, 31st International Conference on Concurrency Theory (CONCUR 2020)


Abstract
Shortest-path games are two-player zero-sum games played on a graph equipped with integer weights. One player, that we call Min, wants to reach a target set of states while minimising the total weight, and the other one has an antagonistic objective. This combination of a qualitative reachability objective and a quantitative total-payoff objective is one of the simplest settings where Min needs memory (pseudo-polynomial in the weights) to play optimally. In this article, we aim at studying a tradeoff allowing Min to play at random, but using no memory. We show that Min can achieve the same optimal value in both cases. In particular, we compute a randomised memoryless ε-optimal strategy when it exists, where probabilities are parametrised by ε. We also show that for some games, no optimal randomised strategies exist. We then characterise, and decide in polynomial time, the class of games admitting an optimal randomised memoryless strategy.

Cite as

Benjamin Monmege, Julie Parreaux, and Pierre-Alain Reynier. Reaching Your Goal Optimally by Playing at Random with No Memory. In 31st International Conference on Concurrency Theory (CONCUR 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 171, pp. 26:1-26:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{monmege_et_al:LIPIcs.CONCUR.2020.26,
  author =	{Monmege, Benjamin and Parreaux, Julie and Reynier, Pierre-Alain},
  title =	{{Reaching Your Goal Optimally by Playing at Random with No Memory}},
  booktitle =	{31st International Conference on Concurrency Theory (CONCUR 2020)},
  pages =	{26:1--26:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-160-3},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{171},
  editor =	{Konnov, Igor and Kov\'{a}cs, Laura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2020.26},
  URN =		{urn:nbn:de:0030-drops-128381},
  doi =		{10.4230/LIPIcs.CONCUR.2020.26},
  annote =	{Keywords: Weighted games, Algorithmic game theory, Randomisation}
}
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