Christine Largouët

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When dealing with real systems, it is unrealistic to suppose that observations can be totally ordered according to their emission dates. The partially ordered observations and the system are thus both represented as finite-state machines (or automata) and the diagnosis formally defined as the synchronized composition of the model with the observations. The(More)
This paper deals with the incremental off-line computation of diagnosis of discrete-event systems. Traditionally, the diagnosis is computed from the global automaton describing the observations emitted by the system on a whole time period. The idea of this paper is to slice this global automaton according to temporal windows and to compute local diagnoses(More)
This paper deals with diagnosing dynamical systems represented by a discrete-event model and more precisely represented in an automata formalism. It shows how model-checking techniques which have been designed for efficiently testing complex real-time systems can be exploited for diagnostic task. This work originates from an application in the monitoring of(More)
The aim of this paper is to propose the use of a dynamic plot model to improve landcover classification on a sequence of images. This new approach consists in representing the plot as a dynamic system and in modeling its evolution (knowledge about crop cycles) using the timed automata formalism. In order to refine results obtained by a traditional(More)
This paper deals with the integration of domain knowledge to improve the landcover classification of a sequence of images. This new approach consists in representing the plot of land as a dynamic system and in modeling its evolution (knowledge about crop cycles, rotations and farmer practices) with the timed automata formalism. The main feature of this work(More)
On-line reconfiguration is the ability to rearrange dynamically the elements of a system to accommodate failure events or new requirements. Due to the modular representation, decentralized discrete-event approach, recently proposed for the diagnosis of systems, is particularly well suited to the diagnosis of reconfigurable systems. The contribution of this(More)
The interest to build ecosystem models is well acknowledged in order to improve the understanding of the sophisticated linkages between humans and natural species embedded within variable local and global environmental contexts. It is especially true when a complex temporal evolution intervenes as in population regulations. Ecological modellers usually(More)
A time-consuming problem encountered both in system diagnosis and planning is that of computing trajectories over a behavioral model. In order to improve the efficiency of this task, there is currently a great interest in using model-checking techniques developed within the area of computer aided verification. In this paper, we propose to represent the(More)
When dealing with real systems, it is unrealistic to suppose that observations can be totally ordered according to their emission dates. The partially ordered observations and the system are thus both represented as finite-state machines (or automata) and the diagnosis formally defined as the synchronized composition of the model with the observations. The(More)
This work stems on the idea that timed automata models and model-checking techniques may bring much in a decision-aid context when dealing with large and interacting qualitative models. In this paper, we focus on two key issues when facing the interpretation and explanation of behavior in real-world systems: the model building and its exploration using(More)