RISC : Détail des Mémoires et Thèses

Résumé : Agents producing, manipulating, exchanging knowledge are forming as a whole a socio-semantic complex system. Studying such knowledge communities offers theoretical challenges, with the perspective of naturalizing further social sciences, as well as practical challenges, with potential applications enabling agents to know the dynamics of the system they are participating in. The present thesis lies within the framework of this research program. Specifically, we aim to know and be able to model the behavior and the dynamics of such a complex system. Alongside and more broadly, we address the question of reconstruction in social science. Reconstruction is a reverse problem consisting fundamentally of two issues: (i) deduce a given high-level observation for the considered system from strictly low-level phenomena; and (ii) reconstruct the evolution of high-level observations from the dynamics of lower-level objects. In this respect, we argue that several significant aspects of the structure of a knowledge community are primarily produced by the co-evolution between agents and concepts. In particular, we address the first reconstruction issue by using Galois lattices to rebuild taxonomies of knowledge communities from low-level observation of relationships between agents and concepts; achieving ultimately an historical description (inter alia field progress, decline, specialization, interaction — merging or splitting). We then micro-found several stylized facts regarding this particular structure, in other words, we find processes at the level of agents that account for the emergence of epistemic community structure. After assessing the empirical interaction and growth processes, and assuming that agents and concepts are co-evolving, we successfully propose a morphogenesis model that rebuilds relevant high-level stylized facts. Finally, we defend a general epistemological point related to the methodology of complex system reconstruction, that will eventually support our choice of a co-evolutionary framework. In this respect, we suggest that a successful rebuilding is basically a claim that some particular high-level stylized facts, observed with high-level instruments (descriptions by epistemologists and experts) can be fully deduced from low-level objects (here, the epistemic network). We hence suggest that some high-level phenomena cannot be explained without a viewpoint change in not only low-level dynamics but also in the design of low-level objects themselves — such as introducing coevolution between agents and concepts.