方法证据记录
Stochastic Dynamic Programming
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Stochastic Dynamic Programming (SDP) — Sequential decision-making under uncertainty via Markov decision processes
分类方法记录 · process-pipeline / simulation
- Bellman, R. (1957). Dynamic Programming. Princeton University Press, Princeton, NJ. · ISBN 9780486428093
- Puterman, M. L. (1994). Markov Decision Processes: Discrete Stochastic Dynamic Programming. John Wiley & Sons, New York. · ISBN 9780471619772
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