Author: Dr. David Lowemann

Adapting to Individual Differences: An Experimental Study of Language Evolution in Heterogeneous Populations

Abstract Variations in language abilities, use, and production style are ubiquitous within any given population. While research on language evolution has traditionally overlooked the potential importance of such individual differences, these can have an important impact on the trajectory of language evolution and ongoing change. To address this gap, we use a group communication game […]

Published on November 5, 2024

Inverting Cognitive Models With Neural Networks to Infer Preferences From Fixations

Abstract Inferring an individual’s preferences from their observable behavior is a key step in the development of assistive decision-making technology. Although machine learning models such as neural networks could in principle be deployed toward this inference, a large amount of data is required to train such models. Here, we present an approach in which a […]

Published on November 5, 2024

Age‐Related Diversification and Specialization in the Mental Lexicon: Comparing Aggregate and Individual‐Level Network Approaches

Abstract The mental lexicon changes across the lifespan. Prior work, aggregating data among individuals of similar ages, found that the aging lexicon, represented as a network of free associations, becomes more sparse with age: degree and clustering coefficient decrease and average shortest path length increases. However, because this work is based on aggregated data, it […]

Published on November 5, 2024