CYBERNARD: A Computational Reconstruction of Claude Bernard's Scientific Discoveries

摘要

With epistemological insight and artificial intelligence techniques, our aim is to reconstruct Claude Bernard’s empirical investigations with a computational model. We suppose that Claude Bernard had in mind what we call “kernel models” that contain the basic physiological concepts upon which Claude Bernard builds his general physiological theory. The “kernel models” provide a simplified view of physiology, where the internal environment – the so-called “milieu int′erieur” –, mainly the blood, plays an essential role. According to this perspective, we assume that the “kernel models” allow Claude Bernard to make some hypotheses and to draw out their logical consequences. More precisely, the role of the “kernel models” is twofold: on the one hand, they help to generate and manage working hypotheses, for instance to enumerate the probable effects of a toxic substance, on the other hand, they derive, by simulation, the most plausible consequences of each of those hypotheses. We shall show how those “kernel models” can be specified using both description logics and multi-agent systems. Then, the paper will explain how it is possible to build, on these “kernel models”, a virtual experiment laboratory, which lets us construct and conduct virtual experiments that play a role similar to the role of thought experiments. More generally, the paper constitutes an attempt to correlate Claude Bernard’s experiments, achieved to corroborate or refute some of his working hypotheses, to virtual experiments emulated on “kernel models”.