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Über dieses Buch

This contributed volume explores the achievements gained and the remaining puzzling questions by applying dynamical systems theory to the linguistic inquiry. In particular, the book is divided into three parts, each one addressing one of the following topics:

1) Facing complexity in the right way: mathematics and complexity
2) Complexity and theory of language
3) From empirical observation to formal models: investigation of specific linguistic phenomena, like enunciation, deixis, or the meaning of the metaphorical phrases

The application of complexity theory to describe cognitive phenomena is a recent and very promising trend in cognitive science. At the time when dynamical approaches triggered a paradigm shift in cognitive science some decade ago, the major topic of research were the challenges imposed by classical computational approaches dealing with the explanation of cognitive phenomena like consciousness, decision making and language. The target audience primarily comprises researchers and experts in the field but the book may also be beneficial for graduate and post-graduate students who want to enter the field.



Complexity and Linguistic Theory: Epistemological Questions


Chapter 1. The Game of Complexity and Linguistic Theorization

Articulating simplicity and complexity is fundamental for any knowledge endeavor. This chapter carries a critical examination of several possible options in linguistics. Starting with the ancient debate between analogist and anomalist grammar schools, we address the following issues: the nomothetic approach as a reduction to simplicity, and research of determinant laws; complexity, replayed in the models of Complex Systems; the notion of emergence, between determinant and reflective judgment; the assessment of Complex Systems as an apparent middle path to Semiolinguistics; a discussion of linguistic theories directly concerned with the issues of meaning and complexity.
David Piotrowski, Y.-M. Visetti

Chapter 2. Continuity in the Interactions Between Linguistic Units

We investigate the notions of continuity and interaction in linguistic models. There is now a quite rich tradition of work based on the hypothesis that natural language is not a discrete model. Instead, continuous models consider word sense, grammar rules and categories as continuous notions: some words are hard to categorize and some rules do not fully apply in certain contexts. Word meaning in context often corresponds to different meanings according to the dictionary. New models have been proposed that provide a more accurate view of these phenomena. Recent advances in natural language processing also support this idea by providing very rich models based on a multi-level representation of the context of use of linguistic items. We describe how these models provide an interesting convergence between linguistic and computational models.
Gilles Col, Rossana De Angelis, Thierry Poibeau

Chapter 3. Modeling Language Change: The Pitfall of Grammaticalization

Language evolution is the subject of various theoretical studies, following two main paths: one, where language is viewed as a code between meanings and forms to express them, with a focus on language as a social convention; and the other defining language as a set of grammatical rules governing the production of utterances, evolution being the outcome of mistakes in the acquisition process. We claim that none of the current models provides a satisfactory account of the grammaticalization phenomenon, a linguistic process by which words acquire a grammatical status. We argue that this limitation is mainly due to the way these models represent language and communication mechanisms. We therefore introduce a new framework, the “grammatheme,” as a tool which formalizes in an unambiguous way different concepts and mechanisms involved in grammaticalization. The model especially includes an inference mechanism triggering new grammaticalization processes. We present promising preliminary results of a numerical implementation and discuss a possible research program based on this framework.
Quentin Feltgen, Benjamin Fagard, Jean-Pierre Nadal

Chapter 4. The Case for Cognitive Plausibility

This chapter is aimed at stressing a condition, i.e., cognitive plausibility, which complex computational psychology should satisfy in order to be compatible with the evidence of neuroscience and biology in general. The required condition says that the psychological (and hence linguistic) computations have to be (1) tractable and (2) fit to the ordinary situations that they are encoding. Brains have to do with concrete contexts, that is, boundaries in space and time and the influence of the associative networks embodied in the individual’s past. They are not idealized machines in front of an idealized world, but flesh and blood in search for life and survival.
Pietro Perconti

Complexity, Semiotics and Enunciation Theory


Chapter 5. System and Structure. Semiotics as Encyclopaedic Theory of Complexity

Semiotics has perhaps missed the complexity train. It missed it when it was an «imperialist discipline» (Cf. Eco 1975: 17), at the heart of the cultural project of many other disciplines who adopted its models and very particular point of view.
Claudio Paolucci

Chapter 6. Hjelmslev and the Stratification of Signs and Language. The Morphodynamical Approaches to Semiotic Complexity

According to Louis Hjelmslev («La stratification du langage», Word, 10:163–188, 1954), the theory of linguistic and semiotic stratification is a way that aims at the convergences of the connections among linguistic activity, natural languages and speech acts into a dynamical system. Hjelmslev think that the relationship between the internal dynamics of the system components and the variations of semiotic forms, set by the social change and its heterogeneity, should be considered in the terms of an osmosis, by refocusing the virtuous circle between use and collective transmission of linguistic and semiotic forms.
Antonino Bondì

Chapter 7. From Topology to Quasi-Topology. The Complexity of the Notional Domain

Notional domains are a privileged metalinguistic construction of the theory of predicative and enunciative operations (henceforth, TOPE).
Francesco La Mantia

Linguistic Complexity: Physics, Computation and Biology


Chapter 8. Fiat Lux Versus Fiat Lumen: Quantum Effects in Linguistic Operations

Classifying the information content of neural spike trains, an uncertainty relation emerges between the bit size of a word and its duration. This uncertainty is ruled by a quantum constant whose numerical value has nothing to do with Planck’s constant.
Fortunato Tito Arecchi

Chapter 9. Two Ways into Complexity

The dynamic hypothesis (DH) about cognition has often been presented as an alternative to the widely popular computational hypothesis (CH) in cognitive science. While the theoretical distance that separates these two approaches may seem to be significant, there are reasons, we argue, to reconsider the relationship between the dynamical and computational ways of understanding the cognition.
Andrea Zeppi

Chapter 10. Language and Brain Complexity

Humans understand their language thanks to brain processes, and one of the most ambitious endeavors  of neurolinguistics is that of bridging the gap between the bare physiology of the brain and linguistic meaning. The aim of this chapter is to elucidate concepts that may help in bridging this gap, through the lens of brain complexity. Unlike several other chapters of this book, our effort is in analyzing complexity in the brain, and in particular, in brain circuits that support language, rather than in language itself, as an abstract entity. The account we offer for brain complexity in relation to language is presented in terms of self-organization, the general phenomenon of the gradual change of local parts of a system, that lead to their interactions become more functional with respect to their initial arrangement. Forms of neural self-organization appear to be essential in scaffolding representations of the external world within cortical areas, and mathematical formulations of self-organization at the level of the cerebral cortex will be described. We will present examples of models based on self-organization that reproduce specific aspects of the semantics of language. These models are examples of a research direction called “neurosemantics”, an enterprise focused on explaining the development of semantics by concentrating on the constituent neural processes.
Alessio Plebe, Vivian M. De La Cruz
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