ACTIVITIES

"Soft computing" is computing in the presence of uncertainty, qualitative informations, partial/contradictory data - in other words, tackling real problems with an approach modeled after human thinking.

Techniques for this task are for instance:

• Fuzzy Systems
• Neural Networks
• Evolutionary Computation
• Machine Learning

Our research activity is focused on the study of these techniques, from the points of view of theory and implementation, and on the application to problems from many areas (including, but not limited to, industrial automation, environmental monitoring, intelligent transportation systems, medical diagnosis).

Current research issues involve the study of ensemble learning machines and the development of a class of "partially possibilistic" classification and clustering methods.