Optimized bayesian dynamic advising : theory and algorithms
著者
書誌事項
Optimized bayesian dynamic advising : theory and algorithms
(Advanced information and knowledge processing)
Springer, c2006
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注記
Includes bibliographical references (p. [511]-521) and index
内容説明・目次
内容説明
A state-of-the-art research monograph providing consistent treatment of supervisory control, by one of the world's leading groups in the area of Bayesian identification, control, and decision making.
目次
Underlying theory.- Approximate and feasible learning.- Approximate design.- Problem formulation.- Solution and principles of its approximation: learning part.- Solution and principles of its approximation: design part.- Learning with normal factors and components.- Design with normal mixtures.- Learning with Markov-chain factors and components.- Design with Markov-chain mixtures.- Sandwich BMTB for mixture initiation.- Mixed mixtures.- Applications of the advisory system.- Concluding remarks.
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