Könyv Partially Observed Markov Decision Processes Vikram Krishnamurthy

Partially Observed Markov Decision Processes

From Filtering to Controlled Sensing

Nyelv: Angol
Kötés: Kemény kötésű
Elérhetőség: Utánnyomás
Megjelenés ismeretlen
43 092 Ft
Covering formulation, algorithms, and structural results, and linking theory to real-world applicati...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
2016
oldal
488
EAN
9781107134607
ISBN
1107134609
Enbook ID
02832865
Súly
1106
Méretek
256 x 184 x 26

Teljes leírás

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. Bringing together research from across the literature, the book provides an introduction to nonlinear filtering followed by a systematic development of stochastic dynamic programming, lattice programming and reinforcement learning for POMDPs. Questions addressed in the book include: when does a POMDP have a threshold optimal policy? When are myopic policies optimal? How do local and global decision makers interact in adaptive decision making in multi-agent social learning where there is herding and data incest? And how can sophisticated radars and sensors adapt their sensing in real time?

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