Some issues about cognitive modelling and functionalism

Abstract

The aim of this paper is to introduce some methodological issues about cognitive explanatory power of AI systems. We use the new concept of mesoscopic functionalism which is based on links between computational complexity theory and functionalism. This functionalism tries to introduce an unique intermediate, mesoscopic, descriptive level based on the key role of heuristics. The enforcement of constraints at this level can assure a cognitive explanatory power which is not guaranteed from mere selection of modelling technique. So we reconsider the discussions about empirical underdetermination of AI systems, proposed especially for classical systems, and about the research of the "right and unique" technique for cognitive modelling. This allows us to consider the several mainstreams of cognitive artificial intelligence as different attempts to resolve underdetermination and thus, in a way, we can unify them as a manifestation of scientific pluralism. © Springer-Verlag Berlin Heidelberg 2007.