Language Evolution and Computation Bibliography

Sociolinguistic studies have demonstrated that centrally-connected and peripheral members of social networks can both propel and impede the spread of linguistic innovations. We use agent-based computer simulations to investigate the dynamic properties of these network roles in a large social influence network, in which diffusion is modeled as the probabilistic uptake of one of several competing variants by agents of unequal social standing. We find that highly-connected agents, structural equivalents of leaders in empirical studies, advance on-going change by spreading competing variants. Isolated agents, or loners, holding on to existing variants are safe-keepers of variants considered old or new depending on the current state of the rest of the population. Innovations spread following a variety of S-curves and stabilize as norms in the network only if two conditions are simultaneously satisfied: (1) the network comprises extremely highly connected and very isolated agents, and (2) agents are biased to pay proportionally more attention to better connected, or popular, neighbors. These findings reconcile competing models of individual network roles in the selection and propagation process of language change, and support Bloomfield's hypothesis that the spread of linguistic innovations in heterogeneous social networks depend upon communication density and relative prestige.

Word-order typology often uses the linear order of binary grammatical pairs in sentences to classify a language. The present paper proposes a method based on dependency treebanks as a typological means. This paper investigates 20 languages using treebanks with different sizes from 16 K to 1 million dependencies. The results show that some languages are more head-initial or head-final than others, but all contain head-initial and head-final elements. The 20 languages can be arranged on a continuum with complete head-initial and head-final patterns as the two ends. Some data about subjectaverb, objectaverb and adjectiveanoun are extracted from the treebanks for comparison with the typological studies based on the traditional means, the results are similar. The investigation demonstrates that the proposed method is valid for positioning a language in the typological continuum and the resources from computational linguistics can also be used in language typology.

In addition to its theoretical impact, the development of molecular biology has brought about the possibility of extraordinary historical progress in the study of phylogenetic classification of different species and human populations (especially cf. Cavalli Sforza et al., 1994, ...

The mathematical model for language competition developed by Abrams and Strogatz allows the evolution of the numbers of monolingual speakers of two competing languages to be estimated. In this paper, we extend the model to examine the role of bilingualism and social structure, neither of which are addressed in the previous model. We consider the impact of two strategies for language maintenance: (1) adjusting the status of the endangered language; and (2) adjusting the availability of monolingual and bilingual educational resources. The model allows us to predict for which scenarios of intervention language maintenance is more likely to be achieved. Qualitative analysis of the model indicates a set of intervention strategies by which the likelihood of successful maintenance is expected to increase.

Three factors contribute to the evolutionary development of an organism: (i) historical accident (the genetic raw material available for natural selection to work on); (ii) adaptation through natural selection; (iii) nonbiological (especially physical) constraints. The same factors apply in principle to characteristics of an organism, such as the biological basis of the capacity for language in humans. From the point of view of these three factors, the author discusses recent contributions from linguists to language evolution research, including the contributions in this volume. He emphasises the importance of language evolution research for the development of linguistic theory, and the consequent need for more linguists to get involved in language evolution research.

For the benefit of linguists new to the field of language evolution, the author sets out the issues that need to be distinguished in any research on it. He offers a guided tour of contemporary approaches, including the work of linguists (Bickerton, Carstairs-McCarthy, Chomsky, Hurford, Jackendoff, Pinker, Wray), animal behaviour experts (Dunbar, Hauser, Premack, Savage-Rumbaugh), neurophysiologists (Arbib, Calvin), psychologists (Corballis, Donald), archaeologists (Davidson), and computer modellers (Batali, Kirby, Steels). He criticises the expectation that recent discoveries such as `mirror neurons' and the FOXP2 gene will provide easy answers. He emphasises the extremely interdisciplinary nature of this field, and also the importance of involvement in it by linguists, after more than a century of neglect.

This paper argues for an alternative answer to Carstairs-McCarthy's (1999) question ``Why do all languages distinguish between NPs and sentences?'' While agreeing on basic philosophical points with Carstairs-McCarthy, such as the lack of a distinction between truth and reference independent of grammar, I argue that the S/NP distinction has its roots in the basic communicative distinction between Topic and Comment. In the very earliest mental processes, long antedating language, binary structure can be found, with components that one can associate with the functions of identifying or locating an object and representing some information about it. When private thought went public, the earliest messages in any code with rudimentary syntax were of similar bipartite structure, with one part conveying information presumed to be already known to the hearer, and identifying the object that the message is about. The other part of the bipartite message conveyed information presumed to be new to the hearer. This bipartite structure, with its concomitant distinction between types of expression that could fulfil the respective roles, was central enough to the main function of public language, namely communication, that it was never eroded away, and is the basis of the bipartite structure found universally in languages today.

We explore the proposal that the linguistic forms and structures employed by our earliest language-using ancestors might have been significantly different from those observed in the languages we are most familiar with today, not because of a biological difference between them and us, but because the communicative context in which they operated was fundamentally different from that of most modern humans. Languages that are used predominantly for esoteric (intra-group) communication tend to have features that are semantically and grammatically 'complex', while those used also (or even exclusively) for exoteric (inter-group) communication become 'simplified' towards rule-based regularity and semantic transparency. Drawing on a range of contemporary data, we propose a psycholinguistic explanation for why esotericity would promote such complexity, and argue that this is the natural default setting for human language. This being so, it should be taken into account when modelling the evolution of language, for some of the features that are normally viewed as fundamental - including the notion of fully developed underlying rule-based systematicity - may, in fact, be cultural add-ons.

The dominant theory of the evolution of complex language from protolanguage can be termed the synthetic approach. Under this view, single words arose first in evolution, and were combined as syntax evolved. More recently, an alternative scenario for protolanguage has been proposed, which we can term the holistic approach. Scholars subscribing to this view propose that words emerge from longer, entirely arbitrary strings of sounds - non-compositional utterances - via a process of fractionation. Such holistic utterances initially have no internal structure, but represent whole messages. The idea is that over time, chance phonetic similarities are observed between sections of utterances, and that if similar meanings can be ascribed to these strings, then 'words' will emerge. This paper dissects the main ideas found in the holistic approach, and argues on a number of grounds that it is conceptually and empirically flawed. A proposal that protolanguage developed out of an earlier holistic primate communication system is hard to sustain, in view of differences between primate vocalization and language. Evidence against the holistic approach is offered on the basis of known facts about the historical development of natural languages, and a conclusion is drawn in favour of synthetic models of protolanguage.

Humans possess a number concept that differs from its predecessors in animal cognition in two crucial respects: (1) it is based on a numerical sequence whose elements are not confined to quantitative contexts, but can indicate cardinal/quantitative as well as ordinal and even nominal properties of empirical objects (e.g. `five buses': cardinal; `the fifth bus': ordinal; `the #5 bus': nominal), and (2) it can involve recursion and, via recursion, discrete infinity. In contrast to that, the predecessors of numerical cognition that we find in animals and human infants rely on finite and iconic representations that are limited to cardinality and do not support a unified concept of number.

In this paper, I argue that the way such a unified number concept could evolve in humans is via verbal sequences that are employed as numerical tools, that is, sequences of words whose elements are associated with empirical objects in number assignments. In particular, I show that a certain kind of number words, namely the counting sequences of natural languages, can be characterised as a central instance of verbal numerical tools.

I describe a possible scenario for the emergence of such verbal numerical tools in human history that starts from iconic roots and that suggests that in a process of co-evolution, the gradual emergence of counting sequences and the development of an increasingly comprehensive number concept supported each other.

On this account, it is language that opened the way for numerical cognition, suggesting that it is no accident that the same species that possesses the language faculty as a unique trait, should also be the one that developed a systematic concept of number.

A strong constraint on the arithmetical combinations allowed in compound numerals, called the Packing Strategy, applies very widely to numeral systems across the world. A previous attempt to explain the existence of the strong universal constraint, in terms of a gradual socio-historical process of standardization, will not scale up to higher-valued numerals. It is proposed that the real explanation for the Packing Strategy is that it reflects two natural principles applied in the practical task of counting objects. These two principles, `Go as far as you can with the resources you have', and `Minimize the number of entities you are dealing with', are not specific to the counting task, but are of more general application to practical tasks.

The computer simulation of language change in a finite, structured population which was presented in an earlier paper ('Using Social Impact Theory to simulate language change', Lingua 108, 95-117, 1999), is here extended to speech communities of different sizes. On the basis of the results it is proposed (a) that language change may be faster in small communities; (b) that linguistic borrowing is one sense more likely in small communities; and (c) that the evolution of linguistically marked structures is more likely in small communities. It is argued that these three generalisations could be used to make sense of the different patterns of linguistic diversity observed in the Old and New Worlds, and the distribution of marked word orders in the world's languages.

This paper presents a framework for simulating language change in social networks derived from Social Impact Theory. In this framework, the language learner samples the speech of individuals from right across his speech community, though he may weight their input differentially according to their social position. This conceptualisation is argued to be more realistic than that provided by other models. Computer simulations are used to investigate the effects on language change of different social structures and biases in language acquisition. From the results of these simulations, it is argued that the fundamental engine driving language change is the combination of inherent variation in language acquisition and differences between individuals in local social influence. Functional biases attaching to different linguistic variants influence the direction of language change.

Most linguistic theories assume lexicon entries which incorporate the idea of the Saussurean sign, a bidirectional mapping between a phonological form and some representation of a concept. This Sign, like grammars generally, is unbiased with respect to perception or production, and provides part of the cognitive map which speakers use both in speaking and in interpreting the utterances of others. This bidirectionality of the Sign, or code, is a design feature of human language although workable communication does not necessarily incorporate such a feature.

Part of the Language Acquisition Device is a mechanism which mentally constructs such a bidirectional mapping, on the basis of observed samples of communicative behaviour (transmission and reception). This basic aspect of the LAD presumably evolved because of its superiority over other conceivable mechanisms for acquiring a basis for communicative behaviour from a sampling of observed transmission and reception data.

Three conceivable strategies for acquiring the basis of communicative behaviour, here labelled the Imitator, Calculator, and Saussurean strategies, are defined as functions from samplings of observed behaviour to acquired behaviour patterns. Essentially, the Imitator imitates the transmission and reception patterns in the observed sample; the Calculator constructs optimal reception responses to the transmissions in the observed sample and optimal transmission responses to receptions in the observed sample; the Saussurean imitates the transmission behaviour in the sample, but shapes his reception behaviour to mirror the acquired transmission behaviour, thus internalizing the equivalent of a set of bidirectional Saussurean signs. Extensive simulations of populations endowed with these innate strategies show the Saussurean strategy to be a winner in evolutionary terms; it produces individuals who communicate more successfully than individuals endowed with the other two strategies.