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Optimized Bayesian Dynamic Advising: Theory and Algorithms (Advanced Information and Knowledge Processing)
 
 
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Optimized Bayesian Dynamic Advising: Theory and Algorithms (Advanced Information and Knowledge Processing) [Hardcover]

Miroslav Karny (Editor)

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Book Description

September 1, 2005 Advanced Information and Knowledge Processing
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.

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From the Back Cover

Written by one of the world’s leading groups in the area of Bayesian identification, control and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. Starting from abstract ideas and formulations, and culminating in detailed algorithms, Optimized Bayesian Dynamic Advising comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modeling by dynamic mixture models and fully probabilistic dynamic optimization. The proposed non-standard problem formulation and its solution mark a significant contribution to the design of anthropocentric automation systems. Written for a broad audience, including developers of algorithms and application engineers, researchers, lecturers and postgraduates, this book can be used as a reference tool, and an advanced text on Bayesian dynamic decision making. The accompanying CD contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the most important and complex areas of the material presented.

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Inside This Book (learn more)
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
ideal pdf, stabilized forgetting, recommended pointers, fully probabilistic design, consistent data blocks, advisory mixture, ideal pelf, bounding mapping, approximate parameter estimation, extended information matrix, objective pdf, parameterized factors, predictive pdfs, mixture initiation, iterative mode, cancelling problem, advising strategy, trial merger, recognizable actions, flattening rate, mixture describing, discrete regressor, prior pdf, posterior pdf, cth component
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Under Agreement, Apply Algorithm
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
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