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Poster
Learning From Small Samples: An Analysis of Simple Decision Heuristics
Özgür Şimşek · Marcus Buckmann

Mon Dec 07 04:00 PM -- 08:59 PM (PST) @ 210 C #11 #None

Simple decision heuristics are models of human and animal behavior that use few pieces of information---perhaps only a single piece of information---and integrate the pieces in simple ways, for example, by considering them sequentially, one at a time, or by giving them equal weight. It is unknown how quickly these heuristics can be learned from experience. We show, analytically and empirically, that only a few training samples lead to substantial progress in learning. We focus on three families of heuristics: single-cue decision making, lexicographic decision making, and tallying. Our empirical analysis is the most extensive to date, employing 63 natural data sets on diverse subjects.

Author Information

Özgür Şimşek (Max Plank Institute for Human Development)
Marcus Buckmann (Max Planck Institute for Human Development)

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