Bounds for the regret loss in dynamic programming under adaptive control

DOI10.1007/BF01916897zbMath0502.90085OpenAlexW2006974531MaRDI QIDQ3968777

Michael Kolonko

Publication date: 1983

Published in: Zeitschrift für Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01916897

zbMATH Keywords

estimation erroradaptive procedureMarkovian dynamic programmingbounds for the expected regret loss

Mathematics Subject Classification ID

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

Related Items (7)

Continuous dependence of stochastic control models on the noise distribution ⋮ On truncations and perturbations of Markov decision problems with an application to queueing network overflow control ⋮ Nonparametric adaptive control of discrete-time partially observable stochastic systems ⋮ Estimation and control in discounted stochastic dynamic programming ⋮ Generalized Lipschitz-continuity of integrals with respect to a parameter of the intergrating probability measure ⋮ First-order sensitivity of the optimal value in a Markov decision model with respect to deviations in the transition probability function ⋮ Adaptive control of Markov processes with incomplete state information and unknown parameters

Cites Work

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• Stochastic optimal control. The discrete time case
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• Strong consistency of a modified maximum likelihood estimator for controlled Markov chains
• Strongly consistent estimation in a controlled Markov renewal model
• Conditions for optimality in dynamic programming and for the limit of n-stage optimal policies to be optimal
• Estimation and control in Markov chains

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