Partially Observed Markov Decision Processes: Filtering, Learning and Controlled Sensing - Tapa dura

Krishnamurthy, Vikram

9781009449434: Partially Observed Markov Decision Processes: Filtering, Learning and Controlled Sensing

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ISBN 10: 1009449435 ISBN 13: 9781009449434

Editorial: Cambridge University Press, 2025

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Covering formulation, algorithms and structural results and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers in engineering, operations research, and economics to understand the underlying unifying themes without getting weighed down by mathematical technicalities. In light of major advances in machine learning over the past decade, this edition includes a new Part V on inverse reinforcement learning as well as a new chapter on non-parametric Bayesian inference (for Dirichlet processes and Gaussian processes), variational Bayes and conformal prediction.

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Vikram Krishnamurthy is Professor of Electrical and Computer Engineering at Cornell University. From 2002 to 2016, he was Professor and Senior Canada Research Chair in Statistical Signal Processing at the University of British Columbia. His research contributions are in statistical signal processing, stochastic optimization and control, with applications in social networks, adaptive radar systems and biological ion channels. He is a Fellow of IEEE and served as Distinguished Lecturer for the IEEE Signal Processing Society and Editor-in-Chief of IEEE Journal of Selected Topics in Signal Processing. He was awarded an honorary doctorate from the Royal Institute of Technology (KTH) Sweden in 2014.

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Editorial: Cambridge University Press
A�o de publicaci�n: 2025
Idioma: Ingl�s
ISBN 10: 1009449435
ISBN 13: 9781009449434
Encuadernaci�n: Tapa dura
N�mero de edici�n: 2
N�mero de p�ginas: 652
Contacto del fabricante: Cambridge University Press
https://www.cambridge.org/

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Partially Observed Markov Decision Processes: Filtering, Learning and Controlled Sensing

Krishnamurthy, Vikram

Publicado por Cambridge University Press, 2025

ISBN 10: 1009449435 ISBN 13: 9781009449434

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Partially Observed Markov Decision Processes : Filtering, Learning and Controlled Sensing

Krishnamurthy, Vikram

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Partially Observed Markov Decision Processes: Filtering, Learning and Controlled Sensing

Krishnamurthy, Vikram

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Partially Observed Markov Decision Processes: Filtering, Learning and Controlled Sensing

Krishnamurthy, Vikram

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Partially Observed Markov Decision Processes: Filtering, Learning and Controlled Sensing

Krishnamurthy, Vikram

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Partially Observed Markov Decision Processes (Hardcover)

Vikram Krishnamurthy

Publicado por Cambridge University Press, Cambridge, 2025

ISBN 10: 1009449435 ISBN 13: 9781009449434

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Hardcover. Condici�n: new. Hardcover. Covering formulation, algorithms and structural results and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers in engineering, operations research, and economics to understand the underlying unifying themes without getting weighed down by mathematical technicalities. In light of major advances in machine learning over the past decade, this edition includes a new Part V on inverse reinforcement learning as well as a new chapter on non-parametric Bayesian inference (for Dirichlet processes and Gaussian processes), variational Bayes and conformal prediction. This survey of formulation, algorithms, and structural results in POMDPs focuses on underlying concepts and connections to real-world applications in controlled sensing, keeping technical machinery to a minimum. The new edition includes inverse reinforcement learning, non-parametric Bayesian inference, variational Bayes and conformal prediction. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de ref. del art�culo: 9781009449434

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