Partially Observed Markov Decision Processes

Discover the intricacies of decision-making under uncertainty with Partially Observed Markov Decision Processes by Vikram Krishnamurthy. Published by Cambridge University Press in 2025, this comprehensive second revised edition spans 651 pages and offers a thorough exploration of formulation, algorithms, and structural results in Partially Observed Markov Decision Processes (POMDPs).

Krishnamurthy expertly focuses on the fundamental concepts while connecting them to real-world applications in controlled sensing, ensuring that technical jargon is kept to a minimum. This updated edition introduces key topics such as inverse reinforcement learning, non-parametric Bayesian inference, variational Bayes, and conformal prediction, making it an essential resource for researchers and practitioners alike. Enhance your understanding of POMDPs and their applications by adding this insightful book to your collection today!