Gérald Rocher | Searcharxiv

arXiv2020

Overview and Challenges of Ambient Systems, Towards a Constructivist Approach to their Modelling

From a closed and controlled environment, neglecting all the external disturbances, information processing systems are now exposed to the complexity and the aleas of the physical environment, open and uncontrolled. Indeed, as envisioned by Mark Weiser as early as 1991, the progresses made on wireless communications, energy storage and the miniaturization of computer components, made it possible the fusion of the physical and digital worlds. This fusion is embodied in a set of concepts such as Internet of Things, Pervasive Computing, Ubiquitous Computing, etc. From a synthesis of these different concepts, we show that beyond the simple collection of environmental data from sensors, the purpose of the information processing systems underlying these concepts is to carry out relevant actions that the processing of these data suggests in our environment. However, due to the complexity of these systems and the inability to predict the effects of their actions, the responsibility for these actions still often remains with users. Mark Weiser's vision of disappearing computing is still far from being a reality. This situation calls for an epistemological rupture that is proposed to be concretized through the systemic approach which finds its foundations in constructivism. It is no longer a question of predicting but of evaluating in vivo the effectiveness of these systems. The perspectives for such an approach are discussed.

cs.CY↗

arXiv2019

Effectiveness Assessment of Cyber-Physical Systems

By achieving their purposes through interactions with the physical world, Cyber-Physical Systems (CPS) pose new challenges in terms of dependability. 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. 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. The TBM is used in conjunction with the Input/Output Hidden Markov Modeling framework (we denote by Ev-IOHMM) to specify the expected evolution of the physical system controlled by the CPS and the tolerances towards uncertainties. The measure of effectiveness is then 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 proposed approach is applied to autonomous vehicles and show how the degree of effectiveness can be used for bench-marking their controller relative to the highway code speed limitations and passengers' well-being constraints, both modeled through an Ev-IOHMM.

cs.AI↗