Language Evolution and Computation Bibliography

It is generally accepted that second language (L2) acquisition becomes more difficult as one grows older and that success in adult L2 acquisition is highly variable. Nevertheless, humans in language contact situations have to cope with intergroup communication. This article examines the ways society has responded to this challenge. It describes eleven strategies or workarounds that humans use to deal with this problem: developing lingua francas, forming Sprachbunds, practicing exogenous marriage, undergoing language shift, learning the target language imperfectly, developing a pidgin or creole, shifting the learning burden to children, relying on individual differences in aptitude among learners, developing the art and practice of translation, developing machine translation technology, and providing instruction. The eleven strategies can be understood as involving four broad societal responses to the burden of SLA: to simplify the learning task, to create a simpler language, to leave it to a special set of learners, and to provide special training. Finally, the article offers some speculations about the evolutionary reasons for the difficulties experienced in adult L2 acquisition.

Language has a fundamentally social function. Processes of human interaction along with domain-general cognitive processes shape the structure and knowledge of language. Recent research in the cognitive sciences has demonstrated that patterns of use strongly affect how language is acquired, is used, and changes. These processes are not independent of one another but are facets of the same complex adaptive system (CAS). Language as a CAS involves the following key features: The system consists of multiple agents (the speakers in the speech community) interacting with one another. The system is adaptive; that is, speakers' behavior is based on their past interactions, and current and past interactions together feed forward into future behavior. A speaker's behavior is the consequence of competing factors ranging from perceptual constraints to social motivations. The structures of language emerge from interrelated patterns of experience, social interaction, and cognitive mechanisms. The CAS approach reveals commonalities in many areas of language research, including first and second language acquisition, historical linguistics, psycholinguistics, language evolution, and computational modeling.

Constituent structure is considered to be the very foundation of linguistic competence and often considered to be innate, yet we show here that it is derivable from the domain-general processes of chunking and categorization. Using modern and diachronic corpus data, we show that the facts support a view of constituent structure as gradient (as would follow from its source in chunking and categorization) and subject to gradual changes over time. Usage factors (i.e., repetition) and semantic factors both influence chunking and categorization and, therefore, influence constituent structure. We take as our example the complex prepositions of English, for instance, on top of, in back of, and in spite of, whose internal constituent structure has been much debated. From observing strong (but not absolute) usage trends in the corpus data, we find that these complex preposition sequences display varying degrees of emerging constituency. We conclude that constituent reanalysis, like language change generally, proceeds gradually.

Language is a complex adaptive system: Speakers are agents who interact with each other, and their past and current interactions feed into speakers' future behavior in complex ways. In this article, we describe the social cognitive linguistic basis for this analysis of language and a mathematical model developed in collaboration between researchers in linguistics and statistical physics. The model has led us to posit two mechanisms of selectionaneutral interactor selection and weighted interactor selectionain addition to neutral evolution and replicator selection (fitness). We describe current results in modeling language change in terms of neutral interactor selection and weighted interactor selection.

All natural languages rely on sentence-level form-meaning associations (i.e., linking rules) to encode propositional content about who did what to whom. Although these associations are recognized as foundational in many different theoretical frameworks (Goldberg, 1995, 2006; Lidz, Gleitman, & Gleitman, 2003; Pinker, 1984, 1989) and areaat least in principlealearnable (Allen, 1997; Morris, Cottrell, & Elman, 2000), very little empirical work has been done to establish that human participants are able to acquire them from the input. In the present work, we provided adult participants with 3 min worth of exposure to a novel syntactic construction and then tested to see what was learned. Experiment 1 established that participants are able to accurately deploy newly acquired linking rules in a forced-choice comprehension task, and that constructional knowledge largely persists over a 1-week period. In Experiment 2, participants were exposed to the linking rules immanent in one of two novel constructions and were asked to describe novel events using their exposure construction. The data indicate that participants were successful in using their exposure construction's linking rules in production, and that performance was equally good regardless of the specifics of the target linking pattern. These results indicate that linking rules can be learned relatively easily by adults, which, in turn, suggests that children may also be capable of learning them directly from the input.

This article presents an analysis of interactions in the usage, structure, cognition, coadaptation of conversational partners, and emergence of linguistic constructions. It focuses on second language development of English verb-argument constructions (VACs: VL, verb locative; VOL, verb object locative; VOO, ditransitive) with particular reference to the following: (a) Construction learning as concept learning following the general cognitive and associative processes of the induction of categories from experience of exemplars in usage obtained through coadapted micro-discursive interaction with conversation partners; (b) the empirical analysis of usage by means of corpus linguistic descriptions of native and nonnative speech and of longitudinal emergence in the interlanguage of second language learners; (c) the effects of the frequency and Zipfian type/token frequency distribution of exemplars within the Verb and other islands of the construction archipelago (e.g., [Subj V Obj Oblpath/loc]), by their prototypicality, their generic coverage, and their contingency of form-meaning-use mapping, and (d) computational (emergent connectionist) models of these various factors as they play out in the emergence of constructions as generalized linguistic schema.

Most current approaches to linguistic structure suggest that language is recursive, that recursion is a fundamental property of grammar, and that independent performance constraints limit recursive abilities that would otherwise be infinite. This article presents a usage-based perspective on recursive sentence processing, in which recursion is construed as an acquired skill and in which limitations on the processing of recursive constructions stem from interactions between linguistic experience and intrinsic constraints on learning and processing. A connectionist model embodying this alternative theory is outlined, along with simulation results showing that the model is capable of constituent-like generalizations and that it can fit human data regarding the differential processing difficulty associated with center-embeddings in German and cross-dependencies in Dutch. Novel predictions are furthermore derived from the model and corroborated by the results of four behavioral experiments, suggesting that acquired recursive abilities are intrinsically bounded not only when processing complex recursive constructions, such as center-embedding and cross-dependency, but also during processing of the simpler, right- and left-recursive structures.

The evolution of language and the evolution of the brain are tightly interlinked. Language evolution represents a special kind of adaptation, in part because language is a complex behavior (as opposed to a physical feature) but also because changes are adaptive only to the extent that they increase either one's understanding of others, or one's understanding to others. Evolutionary changes in the human brain that are thought to be relevant to language are reviewed. The extent to which these changes are a cause or consequence of language evolution is a good question, but it is argued that the process may best be viewed as a complex adaptive system, in which cultural learning interacts with biology iteratively over time to produce language.

Language is a product of both biological and cultural evolution. Clues to the origins of key structural properties of language can be found in the process of cultural transmission between learners. Recent experiments have shown that iterated learning by human participants in the laboratory transforms an initially unstructured artificial language into one containing regularities that make the system more learnable and stable over time. Here, we explore the process of iterated learning in more detail by demonstrating exactly how one type of structureacompositionalityaemerges over the course of these experiments. We introduce a method to precisely quantify the increasing ability of a language to systematically encode associations between individual components of meanings and signals over time and we examine how the system as a whole evolves to avoid ambiguity in these associations and generate adaptive structure.