Language Evolution and Computation Bibliography

We have been conducting large-scale public experiments with artificial robotic agents to explore what the necessary and sufficient prerequisites are for word-meaning pairs to evolve autonomously in a population of agents through a self-organized process. We focus not so much on the question of why language has evolved but rather on how. Our hypothesis is that when agents engage in particular interactive behaviors which in turn require specific cognitive structures, they automatically arrive at a language system. We study this topic by performing experiments based on artificial systems. One such experiment, known as the Talking Heads Experiment, employs a set of visually grounded autonomous robots into which agents can install themselves to play language games with each other.

Using computational modeling techniques, this paper explores the range of conditions under which structured, language-like communication systems can emerge. In particular, we reconsider Simon Kirby's learning bottleneck model of linguistic adaptation using a different learning mechanism and different semantic domain. We demonstrate how parameters such as population size and training corpus size affect the likelihood of a population reaching consensus on a structure communication system.

Introduction

The acquisition and processing of language is governed by a number of universal constraints, many of which undoubtedly derive from innate properties of the human brain. These constraints lead to certain universal tendencies in how languages are structured and used. More generally, the constraints help explain why the languages of the world take up only a small part of the considerably larger space de. ned by the logically possible linguistic subpatterns. Although there is broad consensus about the existence of innate constraints on the way language is acquired and processed, there is much disagreement over whether these constraints are linguistic or cognitive in nature. Determining the nature of these constraints is important not only for theories of language acquisition and processing, but also for theories of language evolution. Indeed, these issues are theoretically intertwined because the constraints on language define the endpoints for evolutionary explanations: theories about how the constraints evolved in the hominid lineage are thus strongly determined by what the nature of these constraints is taken to be.

The Chomskyan approach to language suggests that the constraints on the acquisition and processing of language are linguistic, rather than cognitive, in nature. Th e constraints are represented in the form of a Universal Grammar (UG)--a large biological endowment of linguistic knowledge (e.g. Chomsky 1986). It is assumed that this knowledge-base is highly abstract, comprising a complex set of linguistic rules and principles that could not be acquired from exposure to language during development. Opinions differ about how UG emerged as the endpoint of language evolution. Some researchers have suggested that it evolved through a gradual process of natural selection (e.g., Newmeyer 1991; Pinker 1994; Pinker and Bloom 1990), whereas others have argued for a sudden emergence through non-adaptationist evolutionary processes (e.g., Bickerton 1995; Piattelli-Palmarini 1989). An important point of agreement is the emphasis in their explanations of language evolution on the need for very substantial biological changes to accommodate linguistic structure.

More recently an alternative perspective is gaining ground, advocating a refocus in thinking about language evolution. Rather than concentrating on biological changes to accommodate language, this approach stresses the adaptation of linguistic structures to the biological substrate of the human brain (e.g., Batali 1998; Christiansen 1994; Christiansen and Devlin 1997; Deacon 1997; Kirby 1998, 2000, 2001). Languages are viewed as dynamic systems of communication, subject to selection pressures arising from limitations on human learning and processing. Some approaches within this framework have built in a certain amount of linguistic machinery, such as context-free grammars (Kirby 2000). In this chapter we argue that many of the constraints on linguistic adaptation derive from non-linguistic limitations on the learning and processing of hierarchically organized sequential structure. Th ese mechanisms existed prior to the appearance of language, but presumably also underwent changes aft er the emergence of language. However, the selection pressures are likely to have come not only from language but also from other kinds of complex hierarchical processing, such as the need for increasingly complex manual combinations following tool sophistication. Consequently, many language universals may re. ect nonlinguistic, cognitive constraints on learning and processing of sequential structure rather than an innate UG.