Proceedings of the 1992 IEEE International Symposium on Intelligent Control
DOI: 10.1109/isic.1992.225144
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Optimum design of multiresolutional hierarchical control systems

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Cited by 20 publications
(3 citation statements)
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“…Using ε-entropy for complexity evaluation was demonstrated for a multiresolutional intelligent system [18]. We can anticipate that by using computational complexity as one of the performance measures we can improve the existing system of performance evaluators (metrics).…”
Section: Uncertainty and Complexitymentioning
confidence: 99%
“…Using ε-entropy for complexity evaluation was demonstrated for a multiresolutional intelligent system [18]. We can anticipate that by using computational complexity as one of the performance measures we can improve the existing system of performance evaluators (metrics).…”
Section: Uncertainty and Complexitymentioning
confidence: 99%
“…Thus, not only is i t necessary to have the physical elements of the planning paradigm, a tool for performing the search must also be available. This component is described in [3]. It is also available as one of the options in the procedures library of the package.…”
Section: The First Level: Low Resolution Planning (Trajectory Planning)mentioning
confidence: 99%
“…Thus, complexity of computation was drastically reduced (from 10'' to IO') since at higher resolution a smaller envelope of search could be applied following the results of prior search procedures at lower resolution [3]. It became clear that any space can be tessellated and the concept of search with consecutive refinement was extended into the area of state space search for control purposes [4,51. The method of consecutive refinement is a strategy of hierarchical multiresolutional (multiscale, multigranular) problem solving which is utilized extensively in human decision making [6].…”
Section: Introductionmentioning
confidence: 99%