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Programació Dinàmica per Escenaris de Política×Programació Dinàmica Estocàstica×
CampSimulacióSimulació
FamíliaProcess / pipelineProcess / pipeline
Any d'origen19571957
Autor originalBellman, Richard E.Bellman, R.; formalized for stochastic settings by Puterman, M. L.
TipusSequential optimization with scenario branchingSequential optimization under uncertainty
Font seminalBellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780691079516Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. ISBN: 9780486428093
ÀliesPSDP, Policy-Scenario DP, Scenario-Based Dynamic Programming, Policy DPSDP, Markov Decision Process, MDP, Stochastic DP
Relacionats56
ResumPolicy Scenario Dynamic Programming (PSDP) applies Bellman's recursive optimization framework to a set of pre-specified policy scenarios, enabling decision-makers to compare staged, sequential decisions under distinct future conditions. It decomposes a complex, multi-period policy choice into tractable sub-problems solved backward through time, yielding optimal action sequences for each scenario and a structured basis for scenario comparison.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.
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ScholarGateCompara mètodes: Policy Scenario Dynamic Programming · Stochastic Dynamic Programming. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare