Towards W2T Foundations: Interactive Granular Computing and Adaptive Judgement

Development of methods for Wisdom Web of Things (W2T) should be based on foundations of computations performed in the complex environments of W2T. We discuss some characteristic features of decision making processes over W2T. First of all the decisions in W2T are very often made by different agents on the basis of complex vague concepts and relations among them (creating domain ontology) which are semantically far away from dynamically changing and huge raw data. Methods for approximation of such vague concepts based on information granulation are needed. It is also important to note that the abstract objects represented by different agents are dynamically linked by them with some physical objects and the aim is very often to control performance of computations in the physical world for achieving the target goals. Moreover, the decision making by different agents working in the W2T environment requires mechanisms for understanding (to a satisfactory degree) reasoning performed in natural language on concepts and relations from the domain ontology. We discuss a new computation model, where computations are progressing due to interactions of complex granules (c-granules) linked with the physical objects. C-granules are defined relative to a given agent. We extend the existing Granular Computing (GrC) approach by introducing complex granules (c-granules, for short) making it possible to model interactive computations of agents in complex systems over W2T. One of the challenges in the approach is to develop methods and strategies for adaptive reasoning, called adaptive judgement, e.g., for adaptive control of computations. In particular, adaptive judgement is required in the risk/efficiency management by agents supported by W2T. The discussed approach is a step toward realization of the Wisdom Technology (WisTech) program. The approach was developed over years of work on different real-life projects.