وحـدة : ACASA - Cognitive Agents and Symbolic Machine Learning

Headed by Jean-Gabriel Ganascia, the ACASA team works on cognitive modeling using symbolic artificial intelligence techniques, especially symbolic machine learning, abductive, deductive and inductive models of reasoning, semantic information processing, knowledge representation and symbolic data fusion. In addition, an axe of research is centered on computational epistemology and on computational ethics.

These basic researches lead to a number of applications, including:

• Applications to health in collaboration with hospitals, and, more precisely, automatic interpretation of polysomnographic signals using symbolic information fusion techniques;
• Protection of the privacy and design of recommendation systems with semantic processing;
• Electronic editions, with publishers, making use of semantic processing techniques, natural language processing, text mining and cartography of contents.

In this area, we have implemented the Labex OBVIL (Observatory of the Literary Life) with various teams of Paris-Sorbonne specialized in literature, which opens our activities onto the “digital humanities”.