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

Authors