Bokus
Vikram Krishnamurthy - Partially Observed Markov Decision Processes, Inbunden

Inbunden, Engelska, 2025

Partially Observed Markov Decision Processes

Filtering, Learning and Controlled Sensing

Av Vikram Krishnamurthy

1535 kr

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Beskrivning
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.
Produktinformation
  • Utgivningsdatum: 2025-06-05
  • Mått: 185 x 259 x 40 mm
  • Vikt: 1 400 g
  • Format: Inbunden
  • Språk: Engelska
  • Antal sidor: 651
  • Upplaga: 2
  • Förlag: Cambridge University Press
  • ISBN: 9781009449434
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Mer om författaren

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.

Recensioner i media

'This book uniquely offers a comprehensive treatment of structural results for Partially Observable Markov Decision Processes (POMDPs), utilizing submodularity and stochastic orders. The new edition expands its scope by introducing essential results in nonparametric Bayes, stochastic optimization, and inverse reinforcement learning, making it an invaluable resource as both a textbook and reference.' Bo Wahlberg, KTH Royal Institute of Technology, Sweden

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