Secret Agents: Synthetic Approaches to Language Evolution
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2004
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Swarthmore College. Dept. of Linguistics
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Thesis (B.A.)
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Abstract
Extensive work in the field of synthetic ethology demonstrates that multi-agent
simulation is a useful tool for exploring a multitude of population-based phenomena,
including economics, epidemiology, and language evolution. From a
structured canon of local interactions and low-level rules, complex behaviors
can emerge in a wide range of situations. This notion of 'emergence' is central
to evolutionary studies, biological or otherwise. This paper addresses the current
models of language evolution as put forward by contemporary researchers
and attempts to codify the rules of language modeling. It seeks to modify the
work done by Bart de Boer [7, 6, 8, 10] in self-organizing vowel systems by modifying
certain principles of his simulation. With a few algorithmic changes, I
hope to isolate the clustering mechanism at the heart of the simulation, so that
it may be used in modeling self-organizing systems other than vowel inventories.
Chapter 1 provides an introduction to the study of language evolution, then
outlines the current research in the field and synthesizes the central principles of
synthetic ethology as demonstrated by these systems. Chapter 2 describes the
implementational details of reproducing de Boer's simulation and discusses the
results. Chapter 3 explains the simplified model in terms of algorithmic changes
and organizational consequences. Chapter 4 discusses what can be learned from
these experiments.