Today we are facing a real challenge when coping with the increasingly changing nature of science. First the millions of papers published every year makes clearly impossible for anybody to have an exhaustive knowledge of all the important breakthroughs and developments in every fields of science. This issue is made even more critical by the continuous acceleration of scientific production, which threatens every scholars of information overload (the volume of  publications per year has been multiplied by 2 in the last 12 years). Second, science has always been an ever-changing enterprise. However the pace of change has lately increased considerably. Disciplinary boundaries, which until recently had remained relatively stable and sharp for a long time, have become blurred.  Conceptual structures and hierarchies appear, expand and eventually die. One needs to map the fluctuating landscapes of science.

 

 

The goals of these researches is the reconstruction and visualization of science dynamics. We expect to improve our global understanding of science evolution and develop new tools for our daily interactions with its productions.

Complex systems landscape. Words Evolution Software

The software Words Evolution (WE) implements the algorithms and tools developped by this research project.


Key words: knowledge discovery, data mining, cartography, visualization, electronic corpuses, social media, community detection, semantic web.

These researches aim at modeling social cognition as information processing distributed on a population of agents. One of the main objectives is to provide a formal framework, metamimetic games, for the modeling of endogenous preferences.   

Metamimetic games build on the fact that metacognition and human reflexive capacities are the ground for a new class of mimetic rules, that enables to endogenize the distribution of imitation rules while being human specific. The corresponding concepts of equilibrium — counterfactually stable state — and attractor have been proposed.   

This lead to an interpretation of social differenciation in terms of cultural co-evolution among a set of possible motivations, which departs from the traditional view of optimization indexed to immutable criteria that exist prior to the activity of agents. 

Key words : Social cognition, multi-agents, complex systems, social networks, endogenous preferences, imitation, reflexivity, metacognition, stochastic game theory, cultural co-evolution, social differenciation.
 

Emergence of cooperation with network formation. Comparison between analyticall and multi-agent model [7].

These researches aim at the study and modeling of scientific communities and the process of collective elaboration of scientific theories. These communities are taken as a paradigmatic example of collective and distributed knowledge production and management (as in blogs, wikis, linux, etc.). This work is done within the framework of K. Popper's epistemology.

These researches build on the game Nobel (Chavalarias 1998) and are developed along three axis: mathematics modeling, multi-agent modeling, and experimental economics.

Key words: game theory, multi-agents, evolutionary epistemology, Popper, collective discovery,
distributed cognition, knowledge management

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