Optimization models of natural communication

TL;DR

This paper reviews information theoretic models explaining language patterns like Zipf's law, focusing on principles of mutual information maximization and form entropy minimization, and explores their implications for psycholinguistics and language learning.

Contribution

It provides a comprehensive review of the core components of these models, emphasizing their relevance to language structure and self-organization.

Findings

Models explain Zipf's law and related language patterns.

Linear energy function relates to information compression.

Self-organization may tune language-related information measures.

Abstract

A family of information theoretic models of communication was introduced more than a decade ago to explain the origins of Zipf's law for word frequencies. The family is a based on a combination of two information theoretic principles: maximization of mutual information between forms and meanings and minimization of form entropy. The family also sheds light on the origins of three other patterns: the principle of contrast, a related vocabulary learning bias and the meaning-frequency law. Here two important components of the family, namely the information theoretic principles and the energy function that combines them linearly, are reviewed from the perspective of psycholinguistics, language learning, information theory and synergetic linguistics. The minimization of this linear function is linked to the problem of compression of standard information theory and might be tuned by self-organization.