Interactive Granular Computing: Toward Computing Model for Complex Intelligent Systems

We present an approach based on the Interactive Granular Computing (IGrC) model as the basis for developing foundations of Complex Intelligent Systems, i.e., Intelligent Systems dealing with complex phenomena (IS's).The generalization of GrC to IGrC was proposed to support the design of IS's treated in IGrC as examples of complex granules (c-granules) with control.To make such systems successful, it is necessary to enable such systems to have continuous interaction with the physical world.The control of c-granules aims to properly implement the physical semantics of specified transformations of c-granules in the physical world.This implementation is based on the discovery of relevant configurations of physical objects, which provides the basis for perceiving relevant data about these objects and their interactions through the control of c-granules.Additionally, to create high-quality models that serve as the basis for the behavior of IS's, these configurations must be adaptively adjusted by control to allow for the perception of relevant data used to induce those models.Unlike information granules from GrC, the correct implementation of c-granule transformations cannot be restricted to the abstract space.An important property of the IS's discussed here is that they cannot be separated from interactions with the physical world.Hence, they cannot be confined to an abstract space.In particular, the relevance of IGrC in searching for rough computational building blocks for cognition is discussed.These computational building blocks are modeled by complex granules (c-granules) and their networks.It is also proposed to use IGrC as the basis for developing IS's grounded on cognitive computing. Index Terms-(