Discrete-time Dynamic Programming
Discrete-Time Dynamic Programming is a mathematical optimization method that distinguishes itself by solving sequential decision-making problems through recursive value functions defined over discrete time intervals, thereby enabling optimal policy computation in systems with discrete state and action spaces.
159
Publications
23.3K
Citations
307
Authors
171
Institutions
Publications per year
2017–2026
33
Parents
159
David Blackwell · The Annals of Mathematical Statistics · 1962 · 834 citations
Business, Economics, Mathematics +13
1–5 of 159
307
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171

Chinese Academy of Sciences
Beijing, China
17 h-index
41 publications
4K citations
Shandong Institute of Automation
Jinan, China
12 h-index
29 publications
3K citations

University of Science and Technology Beijing
Beijing, China
8 h-index
15 publications
1.2K citations
University of Chinese Academy of Sciences
Beijing, China
7 h-index
16 publications
1.2K citations
Beijing Academy of Artificial Intelligence
Beijing, China
6 h-index
18 publications
1.4K citations
Institute of Automation
Beijing, China
6 h-index
16 publications
1K citations

Northeastern University
Shenyang, China
5 h-index
11 publications
1K citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
12 publications
379 citations
1–8 of 171
9 publications · 628 citations
9
h-index
7 publications · 734 citations
7
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6 publications · 1.4K citations
6
h-index
5 publications · 710 citations
5
h-index
4 publications · 529 citations
4
h-index
1–5