On modeling cognitive process with granular computing

Exploring mechanism of cognitive process is a valuable means of investigating artificial intelligence. But human beingpsilas perception of cognitive process is very limited so far, and related researches are required to be further deepened. This paper focuses on modeling cognitive process based on theory of granular computing(GrC). First, fundamental principle of GrC is used to analyze cognitive process and establish its model. Secondly, a tolerance relation on vector space(ldquorv_spacerdquo for short) is defined by using a distance fucntion dis, and a tolerance granular space model is established, in which the problem of approximate representation of unknown concept(abstraction of perceptive information) is discussed and analyzed. The analyses show that a given concept, sometimes, is difficult to be learned(i.e., difficult to be accurately represented), so appropriate granular world is required. The solution to this problem involves relationship and transformation between granular worlds. At last, such relationship and transformation are investigated, and many related properties and theorems are deduced, solving the facing problem to some extent. The theory and approach of representation of a concept in a granular world and transformation between different granular worlds are made of support cognitive processpsila granular model.