Constructing Cognitive Reasoning and Decision Making Under Attribute Granular Computing Using Fuzzy Petri Nets

From the philosophical point of view, granular computing (GrC) attempts to abstract and formalize the way of human cognition to extract a structured thinking mode. Fuzzy Petri nets (FPNs) have a strong formal description and fuzzy reasoning abilities, which align with human cognitive thinking. However, the traditional FPNs are challenging to describe the following problems: formally expressing the transformation relations between information granules and information granule levels, and then carrying out formal reasoning and decision making based on cognitive thinking mode. This article introduces the qualitative mapping and the qualitative criterion transformation method to explore this problem. First, the problem of attribute information granulation is discussed by using the equivalence relation of attributes. Second, qualitative mapping is used to express the transformation relationship between information granules. The transformation relationship between attribute information granule levels is realized by qualitative criterion transformation, and the basic algebraic structure of attribute information granules is given. The basic network elements of FPNs can formally describe the relationships between these information granules. Finally, a cognitive reasoning and decision-making model for the formal description of attribute information granules based on the new FPN is constructed, and the proposed case study verifies the feasibility of the proposed method.