What is granular computing? As the author have said in (T.Y. Lin, 2006): There are no mathematically valid formal definitions yet. Informally, any computing theory/technology that involves elements and granules (generalized subsets) may be called granular computing (GrC). Intuitively, elements are the data, and granules are the basic knowledge. So granular computing includes data and knowledge computing/engineering, data mining, knowledge discovery, learning and the uncertainty management (granules of no knowledge). We may lump these subfields into AI-engineering. Here granules are interpreted as generalized subsets that include classical subsets, fuzzy subsets, and sets with neighborhood systems (e.g., the alpha cut as neighborhood systems of the cores). As fuzzy sets are defined by membership functions which are bounded real-valued functions, so we will extend further to all functions, even to generalized functions (e.g. Dirac functions), measures/probabilities, generalized measures (e.g. belief functions)