Franck Varenne

Currently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accordingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epistemology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new simulation activity definition is first applied critically. Then, activity is discussed generally. In epistemology, activity is discussed, in a prospective way, as a possible framework in models of human beliefs and knowledge.

The aim of this paper is to describe and analyze the epistemological justification of a proposal initially made by the bio-mathematician Robert Rosen in 1958. In this theoretical proposal, Rosen suggests using the mathematical concept of « category » and the correlative concept of « natural equivalence » in mathematical modeling applied to living beings. Our questions are the following: according to Rosen, to what extent does the mathematical notion of category give access to more « natural » formalisms in the modeling of living beings? Is the so-called « naturalness » of some kinds of equivalences (which the mathematical notion of category makes it possible to generalize and to put at the forefront) analogous to the naturalness of living systems? Rosen appears to answer « yes » and to ground this transfer of the concept of « natural equivalence » in biology on such an analogy. But this hypothesis, although fertile, remains debatable. Finally, this paper makes a brief account of the later evolution of Rosen’s arguments about this topic. In particular, it sheds light on the new role played by the notion of « category » in his more recent objections against computational models that since the 1990’s are pervading almost every domain of biology.

Since the 1990’s, social sciences are living their computational turn. This paper aims to clarify the epistemological meaning of this turn. To do this, we have to discriminate between different epistemic functions of computation among the diverse uses of computers for modeling and simulating in the social sciences. Because of the introduction of a new – and often more user-friendly – way of formalizing and computing, the question of realism of formalisms and of proof value of computational treatments reemerges. Facing the spreading of computational simulations in all disciplines, some enthusiastic observers are claiming that we are entering a new era of unity for social sciences. Finally, the article shows that the conceptual and epistemological distinctions presented in the first sections lead to a more mitigated position: the transdisciplinary computational turn is a great one, but it is of a methodological nature.

Large sets of elements interacting locally and producing specific architectures reliably form a category that transcends the usual dividing line between biological and engineered systems. We propose to call them morphogenetically architected complex systems (MACS). While taking the emergence of properties seriously, the notion of MACS enables at the same time the design (or “meta-design”) of operational means that allow controlling and even, paradoxically, programming this emergence. To demonstrate our claim, we first show that among all the self-organized systems studied in the field of Artificial Life, the specificity of MACS essentially lies in the close relation between their emergent properties and functional properties. Second, we argue that to be a MACS a system does not need to display more than weak emergent properties. Third, since the notion of weak emergence is based on the possibility of simulation, whether computational or mechanistic via machines, we see MACS as good candidates to help design artificial self-architected systems (such as robotic swarms) but also harness and redesign living ones (such as synthetic bacterial films).

Cet article ne se veut pas un commentaire suivi de la réflexion de Wittgenstein sur les règles. Ce ne sera pas non plus un commentaire de l’interprétation que Kripke fait du « suivi de la règle » chez Wittgenstein. Il ne sera pas davantage une application des thèses de Wittgenstein ni une tentative d’application directe d’une interprétation de ces thèses à l’épistémologie de la simulation du vivant ; ce qui serait, en soi, d’ailleurs contestable. Ce travail vise seulement à approfondir la réflexion sur le statut cognitif de la simulation informatique du vivant. À ce titre, qui est donc essentiellement épistémologique et ciblé, il se veut une suggestion d’interprétation conceptuelle de certaines formes de simulation informatique du vivant, suggestion elle-même adossée à une prolongation de certaines distinctions déjà effectuées par Wittgenstein et ses commentateurs au sujet des règles et de leur suivi. L’objectif est de chercher à voir si, par ce moyen, la simulation informatique du vivant, par contraste avec les pratiques plus traditionnelles de modélisation, ne pourrait pas être plus précisément expliquée et légitimée, dans ses apports épistémologiques, comme dans ses limites aussi.

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological concepts so as to show to what extent authors are right when they focus on some empirical, instrumental or conceptual significance of their model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity obtained through a simulation, section 2 gives the possibility to understand more precisely - and then to justify - the diversity of the epistemological positions presented in section 1. Our final claim is that careful attention to the multiplicity of the denotational powers of symbols at stake in complex models and computer simulations is necessary to determine, in each case, their proper epistemic status and credibility.

The credibility of digital computer simulations has always been a problem. Today, through the debate on verification and validation, it has become a key issue. I will review the existing theses on that question. I will show that, due to the role of epistemological beliefs in science, no general agreement can be found on this matter. Hence, the complexity of the construction of sciences must be acknowledged. I illustrate these claims with a recent historical example. Finally I temperate this diversity by insisting on recent trends in environmental sciences and in industrial sciences.

Que peut bien etre l'informatique pour nous envahir a ce point? Se fondant sur des travaux recents de philosophie de l'informatique, ce livre revient sur la notion de Machine de Turing et sur la These de Church: l'ordinateur peut-il tout simuler? (le vivant, l'esprit). Eclairant les notions de computation et d'abstraction a la lumiere de celles de simulation et d'ontologie, il montre en quoi l'informatique n'est ni simplement une branche des mathematiques, ni une technologie de l'information, mais une technologie des croisements des voies de la reference.