Language Evolution and Computation Bibliography

The article reviews computational studies of language change. Computer models of change are helpful because of the complexity of the behavior involved: an entire population of complex, interacting agents must be accounted for. Computational studies frequently bring to light hidden implications of theories, which make them relevant to the theoretical development of both acquisition and change. Studies of language change have focused on discovering mathematical properties of dynamical systems, or on simulating populations of speakers that interact with one another and change their internal states as a result. Models of lexical (including phonological) and syntactic change are considered. Computational models of change have proved useful tools for testing theories of language change, and will prove more useful as the field matures to include more systematic studies of the effects of varying model parameters in complex simulations.

Large linguistic databases, especially databases having a global coverage, such as the World Atlas of Language Structures, the Automated Similarity Judgment Program, and Ethnologue, are making it possible to systematically investigate many aspects of how languages change and compete for viability. Agent-based computer simulations supplement such empirical data by analyzing the necessary and sufficient parameters for the current global distributions of languages or linguistic features. By combining empirical datasets with simulations and applying quantitative methods, it is now possible to address fundamental questions, such as 'what are the relative rates of change in different parts of languages?', 'why are there a few large language families, many intermediate ones, and even more small ones?', 'do small languages change faster or slower than large ones?', or 'how does the borrowing of words relate to the borrowing of structural features?'

The field of language dynamics encompasses the study and modeling of how languages develop (language evolution), change, and interact (language competition). It contrasts with traditional historical linguistics in several ways: the focus is on the world's linguistic diversity rather than just on specific languages or language families; methods are quantitative rather than qualitative; computer simulations are employed for elucidating situations that are not immediately observable, being too complex or pertaining to prehistory; the data used are systematic ones gathered in large databases rather than data that happen to be available for select languages. A crucial feature of the methodology is the fine-tuning of simulation models through empirical observations of quantitative distributions such as those of speaker populations or of grammatical features shared among languages.