Markov Decision Processes with Incomplete Information and Semiuniform Feller Transition Probabilities

DOI10.1137/21M1442152zbMath1498.90245arXiv2108.09232OpenAlexW3164777109WikidataQ113779024 ScholiaQ113779024MaRDI QIDQ5097394

Eugene A. Feinberg, Pavlo O. Kasyanov, Michael Z. Zgurovsky

Publication date: 23 August 2022

Published in: SIAM Journal on Control and Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2108.09232

zbMATH Keywords

Markov decision processincomplete informationoptimality equationsvalue iterationssemiuniform Feller transition probabilities

Mathematics Subject Classification ID

Dynamic programming (90C39) Markov and semi-Markov decision processes (90C40)

Related Items (3)

Formalization of methods for the development of autonomous artificial intelligence systems ⋮ Semi-uniform Feller stochastic kernels ⋮ Equivalent conditions for weak continuity of nonlinear filters

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Convergence of probability measures and Markov decision models with incomplete information
• Uniform Fatou's lemma
• Markov decision processes with applications to finance.
• Berge's theorem for noncompact image sets
• On essential information in sequential decision processes
• On compactness of the space of policies in stochastic dynamic programming
• Stochastic optimal control. The discrete time case
• Average optimality in dynamic programming on Borel spaces -- unbounded costs and controls
• Incomplete information in Markovian decision models
• On dynamic programming: Compactness of the space of policies
• The critical discount factor for finite Markovian decision processes with an absorbing set
• Adaptive Markov control processes
• MDPs with setwise continuous transition probabilities
• Weak Feller property of non-linear filters
• Optimal control of Markov processes with incomplete state information
• Optimal control of partially observable Markovian systems
• Partially Observable Total-Cost Markov Decision Processes with Weakly Continuous Transition Probabilities
• Average Cost Markov Decision Processes with Weakly Continuous Transition Probabilities
• The Complexity of Markov Decision Processes
• Optimal Infinite-Horizon Undiscounted Control of Finite Probabilistic Systems
• State of the Art—A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms
• Conditions for optimality in dynamic programming and for the limit of n-stage optimal policies to be optimal
• Bayesian dynamic programming
• Reduction of a Controlled Markov Model with Incomplete Data to a Problem with Complete Information in the Case of Borel State and Control Space
• The Optimal Control of Partially Observable Markov Processes over the Infinite Horizon: Discounted Costs
• The Optimal Control of Partially Observable Markov Processes over a Finite Horizon
• Average Optimality in Dynamic Programming with General State Space
• Real Analysis and Probability
• Fatou's Lemma in Its Classical Form and Lebesgue's Convergence Theorems for Varying Measures with Applications to Markov Decision Processes
• Average Cost Markov Decision Processes with Semi-Uniform Feller Transition Probabilities
• Fatou's Lemma for Weakly Converging Probabilities
• On Convergence of Value Iteration for a Class of Total Cost Markov Decision Processes

This page was built for publication: Markov Decision Processes with Incomplete Information and Semiuniform Feller Transition Probabilities