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

Krishnamurthy, Vikram

ISBN 10: 1009449435 / ISBN 13: 9781009449434

Published by Cambridge University Press, 2025

About this Item

Seller Inventory # 410659979

Bibliographic Details

• Title: Partially Observed Markov Decision Processes: Filtering, Learning and Controlled Sensing
• Publisher: Cambridge University Press
• Publication Date: 2025
• Language: English
• ISBN 10: 1009449435
• ISBN 13: 9781009449434
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: New

About this title

Synopsis

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.

About the Author

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.