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In order to be fully self-controlled, a system needs built-in knowledge obtained by refining information as a further processing of data. All these three components, i.e. data, information and knowledge map different hierarchical levels in machine intelligence, with knowledge representing the most complex form. In order to account for diversified situations and issues encountered in control settings embracing both engineering and managerial issues, a generic architecture for Knowledge Base Learning Control System (KBLCS) is proposed.
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