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Детерминистично динамично програмиране×Стохастично динамично програмиране×
ОбластСимулационно моделиранеСимулационно моделиране
СемействоProcess / pipelineProcess / pipeline
Година на възникване19571957
СъздателRichard E. BellmanBellman, R.; formalized for stochastic settings by Puterman, M. L.
ТипExact sequential optimization algorithmSequential optimization under uncertainty
Основополагащ източникBellman, R. E. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780486428093
Други названияDDP, Deterministic DP, Classical Dynamic Programming, Bellman Dynamic ProgrammingSDP, Markov Decision Process, MDP, Stochastic DP
Свързани66
РезюмеDeterministic Dynamic Programming (DDP) is a mathematical optimization technique that decomposes a multi-stage decision problem into a sequence of simpler subproblems, solving them exactly when all system parameters — transition functions, costs, and rewards — are known with certainty. It guarantees a globally optimal policy via Bellman's principle of optimality.Stochastic 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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Deterministic Dynamic Programming · Stochastic Dynamic Programming. Извлечено на 2026-06-15 от https://scholargate.app/bg/compare