Two adaptively stepped monotone algorithms for solving discounted dynamic programming equations

DOI10.1080/01630569308816514zbMath0801.90124OpenAlexW2058625809MaRDI QIDQ4293291

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Publication date: 1 December 1994

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630569308816514

zbMATH Keywords

infinite horizondiscrete timefinite statefinite actiondiscounted, stationary Markov decision processes

Mathematics Subject Classification ID

Sequential statistical methods (62L99) Dynamic programming in optimal control and differential games (49L20) Dynamic programming (90C39) Markov and semi-Markov decision processes (90C40)

Cites Work

• Unnamed Item
• Monotonicity of Mangasarian's iterative algorithm for generalized linear complementarity problems
• Stochastic optimal control. The discrete time case
• Computational methods in optimization. A unified approach.
• Methods of descent for nondifferentiable optimization
• Dual Approximations in Optimal Control
• Singular Stochastic Control Problems Solved by a Sparse Simplex Method
• Adaptive aggregation methods for infinite horizon dynamic programming
• Technical Note—Accelerated Computation of the Expected Discounted Return in a Markov Chain
• A generalization of the linear complementarity problem

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