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Stochastické programování×Dynamické programování×
OborSimulaceOptimalizace
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19571957
TvůrceBellman, R.; formalized for stochastic settings by Puterman, M. L.Richard Bellman
TypSequential optimization under uncertaintyExact combinatorial optimization via recursive decomposition
Původní zdrojBellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780486428093Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6
Další názvySDP, Markov Decision Process, MDP, Stochastic DPDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama
Příbuzné63
ShrnutíStochastic Dynamic Programming (SDP) is a mathematical optimization framework for sequential decision problems where outcomes are partly random. It extends Bellman's principle of optimality to stochastic environments, representing problems as Markov Decision Processes (MDPs) and computing optimal policies by solving recursive value equations over states and time periods.Dynamic Programming (DP) is an exact optimization technique introduced by Richard Bellman in 1957 for solving multi-stage decision problems. It decomposes a complex problem into simpler, overlapping subproblems, solves each subproblem once, and stores the results to avoid redundant computation. Grounded in the Principle of Optimality, DP guarantees globally optimal solutions whenever the problem exhibits overlapping subproblems and optimal substructure.
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ScholarGatePorovnat metody: Stochastic Dynamic Programming · Dynamic Programming. Získáno 2026-06-15 z https://scholargate.app/cs/compare