A review of intelligent control based methodologies for modeling and analysis of hierarchically intelligent systems

Existing methodologies for the modeling and analysis of intelligent systems are discussed and summarized. Limitations of current approaches are presented. Briefly discussed is a combination binary-value, multivalue, fuzzy-set-based methodology for the formulation. organization, and coordination of all possible plan scenarios suitable for executing a requested job. The proposed methodology is suitable for both certain and uncertain environments. This happens because the multivalue possibilistic analysis (based on membership functions) becomes a binary-value probabilistic one (based on probability distribution functions) when well-structured known environments are considered. In either case. the flow of information through the system is explicitly modeled. Planning scenarios are built in a top-down, step-by-step way, whereas performance evaluation is performed in a bottom-up way.<<ETX>>

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