In today's dynamic network environments like smart cities, information evolves in distributed resources and in different forms or modalities. An agent or a system that wants to be actively part of this evolution has to be interactive, adaptive, autonomous and intelligent. The paper presents a new version of a distributed model-framework (called Demos) based on autonomous, intelligent agents with anticipatory responses. The first version of the system was proposed by , and the new features (LG Graphs, SPNs and NNs) were embedded in the version presented here. The Demos model is mainly based on the development of an adaptive distributed knowledge base system. Knowledge is represented in a form of frames with internal stochastic Petri-net graph for local representations (KR). A major advantage for the Demos model having a distributed (possibly across the net) is the adaptive knowledge base. Here the authors present the design of an adaptive knowledge model and its challenge, which lays principally on how to learn new knowledge by synthesising SPN forms, and how to develop anticipatory responses at an agent's site. The development of the Demos prototype has a great range of applicability, such as in autonomous negotiating teams, autonomous distributed units for energy efficient distribution, autonomous multiple mobile robots space exploration and maps generation, autonomous intelligent information agents (WWW), automatic information synthesis and fusion, etc. Here the authors have used this model for management of the electric power on a grid of a smart city.
Intelligent information processing for building university knowledge base
