Finite Horizon Dynamic Programming
Finite Horizon Dynamic Programming is a dynamic programming framework distinguished by a predetermined, fixed number of decision stages over which optimal policies are computed to maximize cumulative rewards within the specified temporal limit.
213
Publications
18.6K
Citations
376
Authors
189
Institutions
Publications per year
2017–2026
32
Parents
213
Nonlinear and Dynamic Programming
Wilfred Candler, G. Hadley · Econometrica · 1966 · 744 citations
Dynamic Programming and Markov Processes.
H. Kaufman, Ronald A. Howard · American Mathematical Monthly · 1961 · 648 citations
Garud Iyengar · Mathematics of Operations Research · 2005 · 563 citations
1–5 of 213
376
Massachusetts Institute of Technology, United States
8 publications · 579 citations
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8
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8
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5
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4
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1–5 of 376
189
Massachusetts Institute of Technology
Cambridge, United States
10 h-index
20 publications
4.3K citations
Shandong Institute of Automation
Jinan, China
7 h-index
15 publications
2.3K citations

Chinese Academy of Sciences
Beijing, China
7 h-index
15 publications
2.1K citations
Purdue University West Lafayette
West Lafayette, United States
6 h-index
11 publications
282 citations
Columbia University
New York, United States
6 h-index
10 publications
1.7K citations

University of Massachusetts Amherst
Amherst Center, United States
5 h-index
7 publications
1.2K citations

University of Science and Technology Beijing
Beijing, China
5 h-index
6 publications
561 citations

Northeastern University
Shenyang, China
5 h-index
11 publications
645 citations
1–8 of 189
15 publications · 629 citations
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14 publications · 840 citations
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12 publications · 764 citations
12
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8 publications · 887 citations
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OR · 7 publications · 805 citations
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