2009
NIPS
NeurIPS 2009
Quantification and the language of thought
Abstract
Many researchers have suggested that the psychological complexity of a concept is related to the length of its representation in a language of thought. As yet, however, there are few concrete proposals about the nature of this language. This paper makes one such proposal: the language of thought allows first order quantification (quantification over objects) more readily than second-order quantification (quantification over features). To support this proposal we present behavioral results from a concept learning study inspired by the work of Shepard, Hovland and Jenkins."
🧭
Keyword Pioneer
— concept learning
🐝
Cross-Pollinator
— Artificial Intelligence, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization
📈
Trend Setter
— Computational Linguistics
🐣
Hot Topic Early Bird
— cognitive modeling