Sampling-based Decision Making
Sampling-Based Decision Making is a decision-making paradigm within the bounded rationality framework that, as a genus, relies on drawing limited samples from available options or outcomes rather than exhaustive evaluation, and, as its differentia, leverages probabilistic heuristics to approximate optimal choices under cognitive or computational constraints.
271
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14.3K
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539
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312
Institutions
Publications per year
2017–2026
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Parents
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One and Done? Optimal Decisions From Very Few Samples
Edward Vul, Noah D. Goodman, Thomas L. Griffiths et al. · Cognitive Science · 2014 · 533 citations
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University College London
London, United Kingdom
8 h-index
20 publications
886 citations

Peking University
Beijing, China
7 h-index
12 publications
330 citations
Max Planck Institute for Human Development
Berlin, Germany
7 h-index
16 publications
348 citations
University of California, Berkeley
Berkeley, United States
6 h-index
9 publications
1.2K citations
Princeton University
Princeton, United States
6 h-index
9 publications
761 citations
George Mason University
Fairfax, United States
6 h-index
7 publications
222 citations

Cornell University
Ithaca, United States
6 h-index
10 publications
318 citations

INSEAD
Fontainebleau, France
6 h-index
6 publications
341 citations
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13 publications · 528 citations
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12 publications · 441 citations
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5 publications · 121 citations
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5 publications · 427 citations
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5 publications · 177 citations
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