Knowledge base learning control system - part 1: generic architecture

Authors:
Aboubekeur Hamdi-Cherif
Affiliations:
Université Ferhat Abbas Setif, Faculty of Engineering, Computer Science Department, Setif, Algeria and Computer College, Computer Science Department, Qassim University, Buraydah, Soudi Arabia
Venue:
AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Year:
2012

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Abstract

Different levels of intelligence hierarchically require data, information and knowledge. Knowledge base control systems (KBCSs) represent an artificial intelligence-based paradigm that accounts for the use, generation and management of knowledge in control systems. As in any intelligent machine, the codification of knowledge in KBCSs is responsible for the performance of anthropomorphic tasks, autonomously or interactively with a human operator in structured or unstructured, familiar or unfamiliar environments. On the basis of the main technologies available to us, including cloud computing, Web and data mining technologies, we describe a generic architecture for numeric/symbolic data processing capable of addressing issues related to the imprecision and incompleteness characteristics of the controlled plant. Some tasks trade-offs as part of the control process are also considered.