Minimum Cost-to-go
Minimum Cost-To-Go is a stochastic optimal control function that, within the context of Stochastic Shortest Path Problems, represents the expected minimum cumulative cost from a given state to reach a goal state under an optimal policy.
22
Publications
1.7K
Citations
49
Authors
29
Institutions
Publications per year
2017–2026
2
Variants
Optimal Cost-to-go
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1–5 of 22
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University of Illinois Urbana-Champaign, United States
2 publications · 68 citations
2
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1–5 of 49
29
University of Connecticut
Storrs, United States
3 h-index
4 publications
330 citations

Radboud University Nijmegen
Nijmegen, The Netherlands
2 h-index
5 publications
209 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
88 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
4 publications
136 citations
University of California San Diego
San Diego, United States
2 h-index
4 publications
1.3K citations
Systems Control (United States)
Iron Mountain, United States
2 h-index
4 publications
444 citations
Texas Instruments (United States)
Dallas, United States
1 h-index
1 publications
12 citations

Osnabrück University
Osnabrück, Germany
1 h-index
2 publications
54 citations
1–8 of 29
2 publications · 280 citations
2
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2 publications · 124 citations
2
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2 publications · 127 citations
2
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1 publications · 26 citations
1
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Conference · 1 publications · 57 citations
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1–5