Optimality Equations
Optimality Equations is a mathematical framework in stochastic shortest path problems that characterizes the minimal expected cost-to-go from each state by satisfying a set of recursive equations derived from dynamic programming principles, distinguishing it from alternative solution methods by explicitly encoding the necessary and sufficient conditions for policy optimality under uncertainty.
507
Publications
33.4K
Citations
916
Authors
496
Institutions
Publications per year
2017–2026
70
507
Optimality analysis of sensor-target localization geometries
Adrian N. Bishop, Barış Fi̇dan, Brian D. O. Anderson et al. · Automatica · 2009 · 466 citations
1–5 of 507
916
Universidad Autónoma Agraria Antonio Narro, Mexico
11 publications · 262 citations
10
h-index
8
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7
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6
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5
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1–5 of 916
496
Stanford University
Stanford, United States
11 h-index
16 publications
852 citations
The University of Texas at Austin
Austin, United States
10 h-index
18 publications
601 citations
University of Michigan
Ann Arbor, United States
10 h-index
25 publications
2K citations
University of Maryland, College Park
College Park, United States
9 h-index
13 publications
1.1K citations

Universidad Autónoma Agraria Antonio Narro
Saltillo, Mexico
9 h-index
9 publications
235 citations

Centre National de la Recherche Scientifique
Paris, France
9 h-index
12 publications
301 citations
Massachusetts Institute of Technology
Cambridge, United States
8 h-index
13 publications
1.6K citations
University of Illinois Urbana-Champaign
Urbana, United States
8 h-index
11 publications
566 citations
1–8 of 496
17 publications · 963 citations
15
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15 publications · 586 citations
14
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14 publications · 1.3K citations
13
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14 publications · 307 citations
12
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10 publications · 216 citations
10
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1–5