# Keeping it simple: Implementation and performance of the proto-principle of adaptation and learning in the language sciences

arXiv: https://arxiv.org/abs/2003.03813 · HTML: https://mlsanity.com/paper/2003.03813/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Mar 2020.

## Built on by (most cited first, 3 of 3)

- [Modeling morphology with Linear Discriminative Learning: considerations and design choices](https://mlsanity.com/paper/2106.07936/) (2021)
- [How trial-to-trial learning shapes mappings in the mental lexicon: Modelling Lexical Decision with Linear Discriminative Learning](https://mlsanity.com/paper/2207.00430/) (2022)
- [Frequency effects in Linear Discriminative Learning](https://mlsanity.com/paper/2306.11044/) (2023)

## Abstract (arXiv)

In this paper we present the Widrow-Hoff rule and its applications to language data. After contextualizing the rule historically and placing it in the chain of neurally inspired artificial learning models, we explain its rationale and implementational considerations. Using a number of case studies we illustrate how the Widrow-Hoff rule offers unexpected opportunities for the computational simulation of a range of language phenomena that make it possible to approach old problems from a novel perspective.