Marie-Odile Cordier

A formal framework for the decentralised diagnosis of large scale discrete event systems and its application to telecommunication networks

We address the problem of diagnosing large discrete event systems. Given a flow of observations from the system, the goal is to explain these observations on-line by identifying and localising possible failures and their consequences across the system. Model-based diagnosis approaches deal with this problem but, apart very recent proposals, either they require the computation of a global model of the system which is not possible with large discrete event systems, or they cannot perform on-line diagnosis. The contribution of this paper is the description and the implementation of a formal framework for the on-line decentralised diagnosis of such systems, framework which is based on the divide and conquer principle and does not require the global model computation. This paper finally describes the use of this framework in the monitoring of a real telecommunication network.

Configurations for inference from causal statements: preliminary report

Our aim is to provide a rigorous logical framework for describing causal relations (involved in reasoning tasks such as diagnosis). We propose a framework which is minimal in that only a few properties, hopefully uncontroversial, are imposed upon it. Our semantics of a causal relation is based on collections of possible cases, called “configurations”. n nWe mention several features which causation makes undesirable despite commonly held beliefs. We show how our logic avoid such pitfalls and generally conforms with a strict view of causation.