INRIA Sophia Antipolis / Laboratoire I3S
Abstract:By achieving their purposes through interactions with the physical world, Cyber Physical Systems (CPS) pose new challenges. Indeed, the evolution of the physical systems they control with transducers can be affected by surrounding physical processes over which they have no control and which may potentially hamper the achievement of their purposes. While it is illusory to hope for a comprehensive model of the physical environment at design time to anticipate and remove faults that may occur once these systems are deployed, it becomes necessary to evaluate their degree of effectiveness in vivo.In this paper, the degree of effectiveness is formally defined and generalized in the context of the measure theory and the mathematical properties it has to comply with are detailed. The measure is developed in the context of the Transferable Belief Model (TBM), an elaboration on the Dempster Shafer Theory (DST) of evidence so as to handle epistemic and aleatory uncertainties respectively pertaining the users expectations and the natural variability of the physical environment. This theoretical framework has several advantages over the probability and the possibility theories. (1) It is built on the Open World Assumption (OWA), (2) it allows to cope with dependent and possibly unreliable sources of information. The TBM is used in conjunction with the Input Output Hidden Markov Modeling framework (IOHMM) to specify the expected evolution of the physical system controlled by the CPS and the tolerances towards uncertainties. The measure of effectiveness is obtained from the forward algorithm, leveraging the conflict entailed by the successive combinations of the beliefs obtained from observations of the physical system and the beliefs corresponding to its expected evolution. The conflict, inherent to OWA, is meant to quantify the inability of the model at explaining observations.
Abstract:This paper describes several results of Wimmics, a research lab which names stands for: web-instrumented man-machine interactions, communities, and semantics. The approaches introduced here rely on graph-oriented knowledge representation, reasoning and operationalization to model and support actors, actions and interactions in web-based epistemic communities. The re-search results are applied to support and foster interactions in online communities and manage their resources.