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Partially Observed Markov Decision Processes

Partially Observed Markov Decision Processes

Filtering, Learning and Controlled Sensing

Inhalt

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.

Bibliografische Angaben

Mai 2025, Englisch
Cambridge Academic
978-1-009-44943-4

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