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The emergence of monotone quantifiers via iterated learning

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Contributors:
  2. Shane Steinert-Threlkeld
  3. Jakub Szymanik

Date created: 2019-05-04 12:04 PM | Last Updated: 2021-02-16 11:12 AM

Identifier: DOI 10.17605/OSF.IO/UME39

Category: Project

Description: This project explores the evolution of the universal of monotonicity in the semantics of quantifiers with the help of a computational model. It combines the iterated learning paradigm with neural networks as a model of learning. This project contains the data that we present in the paper. The code for reproducing the results is available at https://github.com/thelogicalgrammar/NeuralNetIteratedQuantifiers.

Has supplemental materials for The emergence of monotone quantifiers via iterated learning on PsyArXiv

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