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Markovov model×Dynamické programovanie×
OdborSimuláciaOptimalizácia
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19061957
TvorcaAndrei MarkovRichard Bellman
TypProbabilistic state-transition modelExact combinatorial optimization via recursive decomposition
Pôvodný zdrojNorris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6
Ďalšie názvyMarkov Chain, Discrete-Time Markov Chain, DTMC, Markov ProcessDP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama
Príbuzné53
ZhrnutieA Markov Model represents a system as a finite set of states and specifies the probability of moving from one state to another at each time step. By capturing only the current state — not the full history — it enables tractable analysis of complex dynamic processes across health economics, engineering reliability, operations research, and social-science modeling.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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ScholarGatePorovnať metódy: Markov Model · Dynamic Programming. Získané 2026-06-15 z https://scholargate.app/sk/compare