Furman, G and Nitschke, G (2020) Evolving an Artificial Creole, Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2020).
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Abstract
There has been a significant amount of research on computational modeling of language evolution to understand the origins and evolution of communication. However, there has relatively been relatively little computational modeling of environmental factors that enable the evolution of creole languages, specifically, modeling lexical term transmission between intersecting language groups, within the context of artificial creole language evolution. This study used an iterative agent-based naming game simulation to investigate the impact of population size and lexical similarity of interacting language groups on the evolution of an artificial creole lexicon. We applied the synthetic methodology, using agent-based artificial language evolution as an experimental platform to investigate two objectives. First, to investigate the impact of population size of interacting groups (with differing lexicons) on the evolution of a common (creole) lexicon. Second, to evaluate the concurrent impact of lexical similarity between interacting agent groups on the evolution of a creole lexicon.
| Item Type: | Conference paper |
|---|---|
| Subjects: | Computing methodologies > Machine learning |
| Date Deposited: | 03 Dec 2021 11:12 |
| Last Modified: | 03 Dec 2021 11:12 |
| URI: | https://pubs.cs.uct.ac.za/id/eprint/1482 |
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