השוואת שיטות

	תכנון דינמי בייסיאני	תכנון דינמי
תחום	סימולציה	אופטימיזציה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1957 (Bellman DP); Bayesian extensions 1990s–2000s	1957
הוגה השיטה	Bellman, R.; extended by Bayesian frameworks (Duff, Bertsekas)	Richard Bellman
סוג	Sequential optimization with Bayesian belief updating	Exact combinatorial optimization via recursive decomposition
מקור מכונן	Bertsekas, D. P. (1995). Dynamic Programming and Optimal Control. Athena Scientific, Belmont, MA. ISBN: 9781886529267	Bellman, R. (1957). Dynamic Programming. Princeton University Press. ISBN: 978-0-691-07951-6
כינויים	BDP, Bayesian DP, Bayesian sequential optimization, Bayesian stochastic control	DP, Bellman's Principle of Optimality, Recursive Optimization, Dinamik Programlama
קשורות	4	3
תקציר	Bayesian Dynamic Programming (BDP) combines Bellman's dynamic programming framework with Bayesian inference to optimize sequential decisions when transition probabilities or reward structures are unknown. At each stage, the agent updates beliefs about the environment using observed outcomes, then computes an optimal policy that explicitly accounts for both immediate rewards and the value of information gained through exploration.	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.