Language evolution as a constraint on conceptions of a minimalist language faculty

PhD ThesisLanguage appears to be special. Well-rehearsed arguments that appeal to aspects of language acquisition, psycholinguistic processing and linguistic universals all suggest that language has certain properties that distinguish it from other domain general capacities. The most widely discussed theory of an innate, modular, domain specific language faculty is Chomskyan generative grammar (CGG) in its various guises. However, an examination of the history and development of CGG reveals a constant tension in the relationship of syntax, phonology and semantics that has endured up to, and fatally undermines, the latest manifestation of the theory: the Minimalist Program. Evidence from language evolution can be deployed to arrive at a more coherent understanding of the nature of the human faculty for language. I suggest that all current theories can be classed on the basis of two binary distinctions: firstly, that between nativist and non-nativist accounts, and secondly between hypotheses that rely on a sudden explanation for the origins of language and those that rely on a gradual, incremental picture. All four consequent possibilities have serious flaws. By scrutinising the extant cross-disciplinary data on the evolution of hominins it becomes clear that there were two significant periods of rapid evolutionary change, corresponding to stages of punctuated equilibrium. The first of these occurred approximately two million years ago with the speciation event of Homo, saw a doubling in the size, alongside some reorganisation, of hominin brains, and resulted in the first irrefutable evidence of cognitive behaviour that distinguishes the species from that of our last common ancestor with chimpanzees. The second period began seven to eight hundred thousand years ago, again involving reorganisation and growth of the brain with associated behavioural innovations, and gave rise to modern humans by at least two hundred thousand years ago. ii I suggest that as a consequence of the first of these evolutionary breakthroughs, the species Homo erectus was endowed with a proto-‘language of thought’ (LoT), a development of the cognitive capacity evident in modern chimpanzees, accompanied by a gestural, and then vocal, symbolic protolanguage. The second breakthrough constituted a great leap involving the emergence of advanced theory of mind and a fully recursive, creative LoT. I propose that the theory outlined in the Representational Hypothesis (RH) clarifies an understanding of the nature of language as having evolved to represent externally this wholly internal, universal LoT, and it is the latter which is the sole locus of syntax and semantics. By clearly distinguishing between a phonological system for semiotic representation, and that which it represents, a syntactico-semantic LoT, the RH offers a fully logical and consistent understanding of the human faculty for language. Language may have the appearance of domain specific properties, but this is entirely derived from both the nature of that which it represents, and the natural constraints of symbolic representation

Universal Grammar: Wittgenstein versus Chomsky

Daniele Moyal-Sharrock, ‘Universal Grammar: Wittgenstein versus Chomsky’ in M. A. Peters and J. Stickney, eds., A Companion to Wittgenstein on Education: Pedagogical Investigations (Singapore: Springer Verlag, 2017), ISBN: 9789811031342The motivations for the claim that language is innate are, for many, quite straightforward. The innateness of language is seen as the only way to solve the so-called 'logical problem of language acquisition': the mismatch between linguistic input and linguistic output. In this paper, I begin by unravelling several strands of the nativist argument, offering replies as I go along. I then give an outline of Wittgenstein's view of language acquisition, showing how it renders otiose problems posed by nativists like Chomsky – not least by means of Wittgenstein's own brand of grammar which, unlike Chomsky's, does not reside in the brain, but in our practices.Peer reviewe

Using domain specific languages to capture design knowledge for model-based systems engineering

Design synthesis is a fundamental engineering task that involves the creation of structure from a desired functional specification; it involves both creating a system topology as well as sizing the system's components. Although the use of computer tools is common throughout the design process, design synthesis is often a task left to the designer. At the synthesis stage of the design process, designers have an extensive choice of design alternatives that need to be considered and evaluated. Designers can benefit from computational synthesis methods in the creative phase of the design process. Recent increases in computational power allow automated synthesis methods for rapidly generating a large number of design solutions. Combining an automated synthesis method with an evaluation framework allows for a more thorough exploration of the design space as well as for a reduction of the time and cost needed to design a system. To facilitate computational synthesis, knowledge about feasible system configurations must be captured. Since it is difficult to capture such synthesis knowledge about any possible system, a design domain must be chosen. In this thesis, the design domain is hydraulic systems. In this thesis, Model-Driven Software Development concepts are leveraged to create a framework to automate the synthesis of hydraulic systems will be presented and demonstrated. This includes the presentation of a domain specific language to describe the function and structure of hydraulic systems as well as a framework for synthesizing hydraulic systems using graph grammars to generate system topologies. Also, a method using graph grammars for generating analysis models from the described structural system representations is presented. This approach fits in the context of Model-Based Systems Engineering where a variety of formal models are used to represent knowledge about a system. It uses the Systems Modeling Language developed by The Object Management Group (OMG SysML™) as a unifying language for model definition.M.S.Committee Chair: Paredis, Chris; Committee Member: McGinnis, Leon; Committee Member: Schaefer, Dir

Enabling and Measuring Complexity in Evolving Designs using Generative Representations for Artificial Architecture

As the complexity of evolutionary design problems grow, so too must the quality of solutions scale to that complexity. In this research, we develop a genetic programming system with individuals encoded as tree-based generative representations to address scalability. This system is capable of multi-objective evaluation using a ranked sum scoring strategy. We examine Hornby's features and measures of modularity, reuse and hierarchy in evolutionary design problems. Experiments are carried out, using the system to generate three-dimensional forms, and analyses of feature characteristics such as modularity, reuse and hierarchy were performed. This work expands on that of Hornby's, by examining a new and more difficult problem domain. The results from these experiments show that individuals encoded with those three features performed best overall. It is also seen, that the measures of complexity conform to the results of Hornby. Moving forward with only this best performing encoding, the system was applied to the generation of three-dimensional external building architecture. One objective considered was passive solar performance, in which the system was challenged with generating forms that optimize exposure to the Sun. The results from these and other experiments satisfied the requirements. The system was shown to scale well to the architectural problems studied

Faculties and Modularity

While theorizing about mental faculties had been in decline throughout the nineteenth and early twentieth century, cognitivism and classical science brought back questions about the architecture of mind. Within this framework, Jerry Fodor developed a functionalist approach to what he called the “modularity of the mind.” While he believes that cognitive science can only explain the lower faculties of the mind, evolutionary psychology seizes on the notion of modularity and transforms it into the radical claim that the mind is modular all the way up. By comparison, recent approaches that take cognition to be embodied and situated have renewed the radical criticism of faculties or modules that was dominant from the nineteenth century onward. The concept of module is a naturalized successor of the traditional concept of faculty, as this chapter shows, and the debate about modules is centrally a debate about the possibility of naturalizing the mind

Chomsky, Cognitive Science, Naturalism and Internalism

I explore Chomsky's naturalistic stance in cognitive science, his internalism in semantics and his attitude towards evolutionary assumption

Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss

While global patterns of human genetic diversity are increasingly well characterized, the diversity of human languages remains less systematically described. Here we outline the Grambank database. With over 400,000 data points and 2,400 languages, Grambank is the largest comparative grammatical database available. The comprehensiveness of Grambank allows us to quantify the relative effects of genealogical inheritance and geographic proximity on the structural diversity of the world's languages, evaluate constraints on linguistic diversity, and identify the world's most unusual languages. An analysis of the consequences of language loss reveals that the reduction in diversity will be strikingly uneven across the major linguistic regions of the world. Without sustained efforts to document and revitalize endangered languages, our linguistic window into human history, cognition and culture will be seriously fragmented.Genealogy versus geography Constraints on grammar Unusual languages Language loss Conclusio