Decision-theoretic Robot Control
Decision-Theoretic Robot Control is a robotic control framework that uses probabilistic models of actions, states, and outcomes within a utility-based decision-making paradigm to optimize behavior under uncertainty, distinguishing it from reactive or purely geometric approaches by formally integrating beliefs, preferences, and expected utility maximization.
36
Publications
1.2K
Citations
105
Authors
49
Institutions
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2017–2026
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Decision-Theoretic, High-Level Agent Programming in the Situation Calculus
Craig Boutilier, Raymond Reiter, Mikhail Soutchanski et al. · 2000 · 195 citations
Task-Driven Tactile Exploration
Kai-yuh Hsiao, Leslie Pack Kaelbling, Tomás Lozano‐Pérez · 2010 · 69 citations · Full text
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Brown University
Providence, United States
3 h-index
8 publications
215 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
4 publications
351 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
2 publications
117 citations
University of California, Berkeley
Berkeley, United States
2 h-index
7 publications
235 citations
Stanford University
Stanford, United States
2 h-index
4 publications
58 citations
Nagoya University
Nagoya, Japan
1 h-index
1 publications
10 citations
West Virginia University
Morgantown, United States
1 h-index
1 publications
10 citations

Wuhan Institute of Technology
Wuhan, China
1 h-index
2 publications
112 citations
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IJRR · 2 publications · 51 citations
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2 publications · 110 citations
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Repository · 1 publications · 10 citations
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1 publications · 12 citations
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1 publications · 10 citations
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