Language Evolution and Computation Bibliography

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As language users humans possess a culturally transmitted system of unparalleled complexity in the natural world. Linguistics has revealed over the past 40 years the degree to which the syntactic structure of language in particular is strikingly complex. Furthermore, as Pinker and Bloom point out in their agenda-setting paper Natural Language and Natural Selection ``grammar is a complex mechanism tailored to the transmission of propositional structures through a serial interface'' (Pinker and Bloom, 1990, 707). These sorts of observations, along with influential arguments from linguistics and psychology about the innateness of language (see, e.g. Chomsky, 1986; Pinker, 1994), have led many authors to the conclusion that an explanation for the origin of syntax must invoke neo-Darwinian natural selection.

``Evolutionary theory offers clear criteria for when a trait should be attributed to natural selection: complex design for some function, and the absence of alternative processes capable of explaining such complexity. Human language meets these criteria.'' (Pinker and Bloom, 1990, 707)

Since Pinker and Bloom made these arguments there have been many attempts to put forward a coherent evolutionary story that would allow us to derive known features of syntax from communicative selection pressures (e.g. Nowak, Plotkin, and Jansen, 2000; Newmeyer, 1991 and discussion in Kirby, 1999a). One problem with this approach to evolutionary lin- guistics is that it often fails to take into account that biological natural selection is only one of the complex adaptive systems at work.

Language emerges at the intersection of three complex adaptive systems:

• Learning: During ontogeny children adapt their knowledge of language in response to the environment in such a way that they optimise their ability to comprehend others and to produce comprehensible utterances.
• Cultural evolution: On a historical (or glossogenetic) timescale, languages change. Words enter and leave the language, meanings shift, and phonological and syntactic rules ad- just.
• Biological evolution: The learning (and processing) mechanisms with which our species has been equipped for language, adapt in response to selection pressures from the environ- ment, for survival and reproduction.

There are two problems with this multiplicity of dynamical systems involved in linguistic evolution. Firstly, we understand very little about how learning, culture, and evolution inter- act (though, see Belew, 1990; Kirby and Hurford, 1997; Boyd and Richerson, 1985), partly because language is arguably the only sophisticated example of such a phenomenon. There clearly are interactions: for example, biological evolution provides the platform on which learning takes place, what can be learnt influences the languages that can persist through cultural evolution, and the structure of the language of a community will influence the selec- tion pressures on the evolving language users (see figure 1).

Secondly, it is not clear what methodology we should use to study this problem. Mathe- matical techniques for looking at the interaction of dynamical systems and linguistic behaviour are in their infancy (though, Nowak, Komarova, and Niyogi, 2001, take a potentially valuable approach). We feel that computational modelling is currently the most appropriate method- ology, but although simulations of language learning have a long history, and there are many methods from the A-life field that can be used for modelling evolution, models of the cultural transmission of learned behaviour are relatively sparse (see Steels, 1997 for a review). This is unfortunate, since we will argue in this chapter that it is through this particular mechanism that the most basic features of human language syntactic structure can be explained.

To remedy this situation, we introduce here the Iterated Learning Model (ILM), a gen- eral approach to exploring the transmission over a glossogenetic timescale of observationally learned behaviour. We will illustrate the ILM with a few examples of simulations that lead to two conclusions:

• There is a non-trivial mapping between the set of learnable languages (i.e. the lan- guages allowed by our innate language faculty), and the set of stable languages (i.e., the languages we can actually expect to see in the world).
• Under certain circumstances, cultural evolution leads inevitably to recursively compo- sitional (i.e., syntactic) languages.

Scholars studying the origins and evolution of language are also interested in the general issue of the evolution of cognition. Language is not an isolated capability of the individual, but has intrinsic relationships with many other behavioral, cognitive, and social abilities. ...

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references. ... Harler P. Evans C, Hauser M (1992) Animal signals: Motivational, referential, or both? In: ...