Nathalie Bertrand

Morgan Abily, Olivier Delestre, Laura Amossé et al.

High resolution (infra-metric) topographic data, including photogram-metric born 3D classified data, are becoming commonly available at large range of spatial extend, such as municipality or industrial site scale. This category of dataset is promising for high resolution (HR) Digital Surface Model (DSM) generation, allowing inclusion of fine above-ground structures which might influence overland flow hydrodynamic in urban environment. Nonetheless several categories of technical and numerical challenges arise from this type of data use with standard 2D Shallow Water Equations (SWE) based numerical codes. FullSWOF (Full Shallow Water equations for Overland Flow) is a code based on 2D SWE under conservative form. This code relies on a well-balanced finite volume method over a regular grid using numerical method based on hydrostatic reconstruction scheme. When compared to existing industrial codes used for urban flooding simulations, numerical approach implemented in FullSWOF allows to handle properly flow regime changes, preservation of water depth positivity at wet/dry cells transitions and steady state preservation. FullSWOF has already been tested on analytical solution library (SWASHES) and has been used to simulate runoff and dam-breaks. FullSWOFs above mentioned properties are of good interest for urban overland flow. Objectives of this study are (i) to assess the feasibility and added values of using HR 3D classified topographic data to model river overland flow and (ii) to take advantage of FullSWOF code properties for overland flow simulation in urban environment.

Nathalie Bertrand, Patricia Bouyer, Gaëtan Staquet

Concurrent parameterized games involve a fixed yet arbitrary number of players. They are described by finite arenas in which the edges are labeled with languages that describe the possible move combinations leading from one vertex to another (n players yield a word of length n). Previous work showed that, when edge labels are regular languages, one can decide whether a distinguished player, called Eve, has a strategy to ensure a reachability objective, against any strategy profile of her arbitrarily many opponents. This decision problem is known to be PSPACE-complete. A basic ingredient in the PSPACE-membership proof is the reduction to the exponential-size knowledge game, a 2-player game that reflects the knowledge Eve has on the number of opponents. In this paper, we provide a symbolic approach, based on antichains, to compute Eve's winning region in the knowledge game. In words, it gives the minimal knowledge Eve needs at every vertex to win the concurrent parameterized reachability game. More precisely, we propose two fixed-point algorithms that compute, as an antichain, the maximal elements of the winning region for Eve in the knowledge game. We implemented these two algorithms in C++, as well as the one initially proposed, and report on their relative performances on various benchmarks.

Nathalie Bertrand, Maëlle Gautrin, Julie Parreaux

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.

Nathalie Bertrand, Pranav Ghorpade, Sasha Rubin

Traditional model-checking techniques typically verify distributed algorithms only for a fixed number of finite-state processes. Parameterized model checking generalizes this to any number of processes, while still typically assuming that each process is finite-state. In this work, we consider asynchronous round-based distributed algorithms in which each process is infinite-state since it can execute for an infinite number of rounds. We show that the parameterized verification problem for asynchronous round-based distributed algorithms is undecidable, already for simple specifications. Nevertheless, as our main contribution, we provide a reduction to LTL model checking over finite-counter systems and prove that it is sound and complete. This enables the use of off-the-shelf, mature symbolic model checkers for finite-counter systems. We demonstrate the practical applicability of this reduction by verifying safety and liveness properties of several asynchronous round-based consensus and leader-election algorithms using the nuXmv model checker.

Nathalie Bertrand, Miheer Dewaskar, Blaise Genest et al.

We introduce a new setting where a population of agents, each modelled by a finite-state system, are controlled uniformly: the controller applies the same action to every agent. The framework is largely inspired by the control of a biological system, namely a population of yeasts, where the controller may only change the environment common to all cells. We study a synchronisation problem for such populations: no matter how individual agents react to the actions of the controller , the controller aims at driving all agents synchronously to a target state. The agents are naturally represented by a non-deterministic finite state automaton (NFA), the same for every agent, and the whole system is encoded as a 2-player game. The first player (Controller) chooses actions, and the second player (Agents) resolves non-determinism for each agent. The game with m agents is called the m-population game. This gives rise to a parameterized control problem (where control refers to 2 player games), namely the population control problem: can Controller control the m-population game for all $m $\in$ N$ whatever Agents does? In this paper, we prove that the population control problem is decidable, and it is a EXPTIME-complete problem. As far as we know, this is one of the first results on parameterized control. Our algorithm, not based on cutoff techniques, produces winning strategies which are symbolic, that is, they do not need to count precisely how the population is spread between states. We also show that if there is no winning strategy, then there is a population size M such that Controller wins the m-population game if and only if $m $\le$ M$. Surprisingly, M can be doubly exponential in the number of states of the NFA, with tight upper and lower bounds.