Julie Parreaux | Searcharxiv

arXiv2026

Reaching as Cheap as Possible in 1-clock Robust Weighted Timed Games

The value problem for 2-player games on graph generally consists in determining the minimal value Min can ensure against any possible strategy for Max. We consider here the value problem for reachability objectives in weighted timed games (WTGs) under a robust semantics. WTGs are a modelling formalism combining real-time constraints and integer weights on transitions and locations in an adversarial setting. Robustness allows for representing timing imprecisions in the measurement of delays and clock values. Robust weighted timed games have been introduced more than a decade ago: they are undecidable in general, and were quite recently shown decidable for the subclasses of acyclic or divergent robust WTGs. This paper pursues the goal of identifying decidable subclasses and establishes the decidability of the robust value problem for 1-clock WTGs.

cs.GT↗

arXiv2026

One-clock synthesis problems

We study a generalisation of Büchi-Landweber games to the timed setting. The winning condition is specified by a non-deterministic timed automaton, and one of the players can elapse time. We perform a systematic study of synthesis problems in all variants of timed games, depending on which player's winning condition is specified, and which player's strategy (or controller, a finite-memory strategy) is sought. As our main result we prove ubiquitous undecidability in all the variants, both for strategy and controller synthesis, already for winning conditions specified by one-clock automata. This strengthens and generalises previously known undecidability results. We also fully characterise those cases where finite memory is sufficient to win, namely existence of a strategy implies existence of a controller. All our results are stated in the timed setting, while analogous results hold in the data setting where one-clock automata are replaced by one-register ones.

cs.FL↗

arXiv2025

Playing Stochastically in Weighted Timed Games to Emulate Memory

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 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 a definition of the expected value in weighted timed games. We then show that, in divergent weighted timed games as well as in (untimed) weighted games (that we call shortest-path games in the following), 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.

cs.GT↗

arXiv2025

Decidability of One-Clock Weighted Timed Games with Arbitrary Weights

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 WTGs have 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).

cs.GT↗

arXiv2024

Synthesis of Robust Optimal Strategies in Weighted Timed Games

Weighted Timed Games (WTG for short) are the most widely used model to describe controller synthesis problems involving real-time issues. The synthesized strategies rely on a perfect measure of time elapse, which is not realistic in practice. In order to produce strategies tolerant to timing imprecisions, we rely on a notion of robustness first introduced for timed automata. More precisely, WTGs are two-player zero-sum games played in a timed automaton equipped with integer weights in which one of the players, that we call Min, wants to reach a target location while minimising the cumulated weight. In this work, we equip the underlying timed automaton with a semantics depending on some parameter (representing the maximal possible perturbation) in which the opponent of Min can in addition perturb delays chosen by Min. The robust value problem can then be stated as follows: given some threshold, determine whether there exists a positive perturbation and a strategy for Min ensuring to reach the target, with an accumulated weight below the threshold, whatever the opponent does. We provide the first decidability result for this robust value problem by computing the robust value function, in a parametric way, for the class of divergent WTGs (introduced to obtain decidability of the (classical) value problem in WTGs without bounding the number of clocks). To this end, we show that the robust value is the fixpoint of some operators, as is classically done for value iteration algorithms. We then combine in a very careful way two representations: piecewise affine functions introduced in [1] to analyse WTGs, and shrunk Difference Bound Matrices considered in [29] to analyse robustness in timed automata. Last, we also study qualitative decision problems and close an open problem on robust reachability, showing it is EXPTIME-complete for general WTGs.

cs.GT↗

arXiv2023

Counterfactual Causality for Reachability and Safety based on Distance Functions

Investigations of causality in operational systems aim at providing human-understandable explanations of why a system behaves as it does. There is, in particular, a demand to explain what went wrong on a given counterexample execution that shows that a system does not satisfy a given specification. To this end, this paper investigates a notion of counterfactual causality in transition systems based on Stalnaker's and Lewis' semantics of counterfactuals in terms of most similar possible worlds and introduces a novel corresponding notion of counterfactual causality in two-player games. Using distance functions between paths in transition systems, this notion defines whether reaching a certain set of states is a cause for the violation of a reachability or safety property. Similarly, using distance functions between memoryless strategies in reachability and safety games, it is defined whether reaching a set of states is a cause for the fact that a given strategy for the player under investigation is losing. The contribution of the paper is two-fold: In transition systems, it is shown that counterfactual causality can be checked in polynomial time for three prominent distance functions between paths. In two-player games, the introduced notion of counterfactual causality is shown to be checkable in polynomial time for two natural distance functions between memoryless strategies. Further, a notion of explanation that can be extracted from a counterfactual cause and that pinpoints changes to be made to the given strategy in order to transform it into a winning strategy is defined. For the two distance functions under consideration, the problem to decide whether such an explanation imposes only minimal necessary changes to the given strategy with respect to the used distance function turns out to be coNP-complete and not to be solvable in polynomial time if P is not equal to NP, respectively.

cs.LO↗

arXiv2023

Counterfactual Causality for Reachability and Safety based on Distance Functions

Investigations of causality in operational systems aim at providing human-understandable explanations of why a system behaves as it does. There is, in particular, a demand to explain what went wrong on a given counterexample execution that shows that a system does not satisfy a given specification. To this end, this paper investigates a notion of counterfactual causality in transition systems based on Stalnaker's and Lewis' semantics of counterfactuals in terms of most similar possible worlds and introduces a novel corresponding notion of counterfactual causality in two-player games. Using distance functions between paths in transition systems, this notion defines whether reaching a certain set of states is a cause for the violation of a reachability or safety property. Similarly, using distance functions between memoryless strategies in reachability and safety games, it is defined whether reaching a set of states is a cause for the fact that a given strategy for the player under investigation is losing. The contribution of the paper is two-fold: In transition systems, it is shown that counterfactual causality can be checked in polynomial time for three prominent distance functions between paths. In two-player games, the introduced notion of counterfactual causality is shown to be checkable in polynomial time for two natural distance functions between memoryless strategies. Further, a notion of explanation that can be extracted from a counterfactual cause and that pinpoints changes to be made to the given strategy in order to transform it into a winning strategy is defined. For the two distance functions under consideration, the problem to decide whether such an explanation imposes only minimal necessary changes to the given strategy with respect to the used distance function turns out to be coNP-complete and not to be solvable in polynomial time if P is not equal to NP, respectively.

cs.LO↗

arXiv2021

Reaching Your Goal Optimally by Playing at Random

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 setting 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 $\varepsilon$-optimal strategy when it exists, where probabilities are parametrised by $\varepsilon$. We then characterise, and decide in polynomial time, the class of games admitting an optimal randomised memoryless strategy.

cs.GT↗