Hierarchically Intelligent Machines
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Hierarchically Intelligent Machines
Author: George N. Saridis
language: en
Publisher: World Scientific
Release Date: 2001-01-01
This book presents the result of 30 years'' work on the original material related to OC thinking machinesOCO, a subject initiated by the author and his colleagues. It is based on the ability of the computer to represent the hierarchical procedure of task conception and execution found in human beings. It is arranged in three levels representing the structure of organizational systems: organization, coordination and execution. Hierarchically Intelligent Machines can serve as a guide to modern intelligent robots. Contents: Machine Intelligence, Knowledge and Precision; Concepts and Definitions; Entropy and the Principle of Increasing Precision with Decreasing Intelligence (IDPI); The Analytic Formulation of Hierarchically Intelligent Machines; Hierarchically Intelligent Control: The Organization Level; Hierarchically Intelligent Control: The Coordination Level; Hierarchically Intelligent Control: The Execution Level; Hierarchically Intelligent Control: Application to Robotic Systems; Intelligent Manufacturing. Readership: Researchers in computer engineering."
Hierarchically Intelligent Machines
This book presents the result of 30 years' work on the original material related to “thinking machines”, a subject initiated by the author and his colleagues. It is based on the ability of the computer to represent the hierarchical procedure of task conception and execution found in human beings. It is arranged in three levels representing the structure of organizational systems: organization, coordination and execution. Hierarchically Intelligent Machines can serve as a guide to modern intelligent robots.
Design Of Intelligent Control Systems Based On Hierarchical Stochastic Automata
In recent years works done by most researchers towards building autonomous intelligent controllers frequently mention the need for a methodology of design and a measure of how successful the final result is. This monograph introduces a design methodology for intelligent controllers based on the analytic theory of intelligent machines introduced by Saridis in the 1970s. The methodology relies on the existing knowledge about designing the different sub-systems composing an intelligent machine. Its goal is to provide a performance measure applicable to any of the sub-systems, and use that measure to learn on-line the best among the set of pre-designed alternatives, given the state of the environment where the machine operates. Different designs can be compared using this novel approach.