Plant and animal species are information-processing entities of such complexity, integration, and adaptive competence that it may be scientifically fruitful to consider them intelligent. The possibility arises from the analogy between learning and evolution, and from recent developments in evolutionary science, psychology and cognitive science. Species are now described as spatiotemporally localized individuals in an expanded hierarchy of biological entities. Intentional and cognitive abilities are now ascribed to animal, human, and artificial intelligence systems that process information adaptively, and that manifest (...) problem-solving abilities. The structural and functional similarities between such systems and species are extensive, although they “are usually obscured by population-genetic metaphors that have nonetheless contributed much to our understanding of evolution.In this target article, I use Sewall Wright's notion of the “adaptive landscape” to compare the performances of evolving species to those of intelligent organisms. With regard to their adaptive achievements and the kinds of processes by which they are achieved, biological species compare very favorably to intelligent animals by virtue of interactions between populations and their environments, between ontogeny and phylogeny, and between natural, interdemic, organic, and species selection. Addressing the question of whether species are intelligent could help to refine our ideas about species, evolution, and intelligence, and could open new lines of empirical and theoretical inquiry in many disciplines. (shrink)

Western science claims to provide unique, objective information about the world. This is supported by the observation that peoples across cultures will agree upon a common description of the physical world. Further, the use of scientific instruments and mathematics is claimed to enable the objectification of science. In this work, carried out by reviewing the scientific literature, the above claims are disputed systematically by evaluating the definition of physical reality and the scientific method, showing that empiricism relies ultimately upon the (...) human senses for the evaluation of scientific theories and that measuring instruments cannot replace the human sensory system. Nativist and constructivist theories of human sensory development are reviewed, and it is shown that nativist claims of core conceptual knowledge cannot be supported by the findings in the literature, which shows that perception does not simply arise from a process of maturation. Instead, sensory function requires a long process of learning through interactions with the environment. To more rigorously define physical reality and systematically evaluate the stability of perception, and thus the basis of empiricism, the development of the method of dimension analysis is reviewed. It is shown that this methodology, relied upon for the mathematical analysis of physical quantities, is itself based upon empiricism, and that all of physical reality can be described in terms of the three fundamental dimensions of mass, length and time. Hereafter the sensory modalities that inform us about these three dimensions are systematically evaluated. The following careful analysis of neuronal plasticity in these modalities shows that all the relevant senses acquire from the environment the capacity to apprehend physical reality. It is concluded that physical reality is acquired rather than given innately, and leads to the position that science cannot provide unique results. Rather, those it can provide are sufficient for a particular environmental setting. (shrink)

Following the development of the selectionist theory of the immune system, there was an attempt to characterize many biological mechanisms as being "selectionist" as juxtaposed to "instructionist." But this broad definition would group Darwinian evolution, the immune system, embryonic development, and Chomsky's language-acquisition mechanism as all being "selectionist." Yet Chomsky's mechanism (and embryonic development) are significantly different from the selectionist mechanisms of biological evolution or the immune system. Surprisingly, there is a very abstract way using two dual mathematical logics to (...) make the distinction between genuinely selectionist mechanisms and what are better called "generative" mechanisms. This note outlines that distinction. (shrink)

During the first two years of human life a common neural substrate underlies the hierarchical organization of elements in the development of speech as well as the capacity to combine objects manually, including tool use. Subsequent cortical differentiation, beginning at age two, creates distinct, relatively modularized capacities for linguistic grammar and more complex combination of objects. An evolutionary homologue of the neural substrate for language production and manual action is hypothesized to have provided a foundation for the evolution of language (...) before the divergence of the hominids and the great apes. Support comes from the discovery of a Broca's area homologue and related neural circuits in contemporary primates. In addition, chimpanzees have an identical constraint on hierarchical complexity in both tool use and symbol combination. Their performance matches that of the two-year-old child who has not yet developed the neural circuits for complex grammar and complex manual combination of objects. (shrink)

Wilkins & Wakefield suggest that changes in the hominid brain made it uniquely “preadaptive” for language, yet no precursor functions served as adaptive substrates to the emergence of language. We present contrary evidence that the ability to discriminate and process rapid and complex auditory information is a cross-species function subserving communication processes including, but not limited to, human speech perception. We suggest that auditory temporal processing served as an evolutionary precursor to speech processing and consequent language development in humans.

Inferences made from endocasts of fossil skulls cannot provide information on the function of particular neocortical areas or the subcortical pathways to prefrontal cortex that form part of the neural substrate for speech, syntax, and certain aspects of cognition. The neural bases of syntax cannot be disassociated from “communication.” Manual motor control was probably a preadaptive factor in the evolution of humansyntactic ability, but neurophysiological data on living humans show that speech motor control and syntax are more closely linked. The (...) evolution of fully modern speech occurred fairly recently; thoughHomo habilismay have had some degree of speech and syntactic ability, it was not fully modern. Stone tools are uncertain indices of language or cognition. (shrink)

L2 learners may access UG principles because these are realized in all natural languages. Since this is not the case for the parametrized aspects of language, parameter setting may be progressively replaced by restructuring mechanisms which are specifically related to the process of representational redescription because L2 learners are not sensitive to the [±] features which define parameters.

Epstein et al. attribute second language learning to the forces of transfer and language universals. They show that transfer is minimally involved in certain types of learning and therefore conclude that universals are involved. However, they forget to consider the important role of learning in second language acquisition.

The role of metalinguistic ability in L2 development is seriously underestimated. It may be seen both (1) as a means of initiating or boosting the flow of primary linguistic data and (2) as a generator of substitute knowledge (derived, but epistemologically distinct from domain-specific knowledge) that may compete with or compensate for perceived gaps in the learners current underlying competence. It cannot serve as a simple means of distinguishing the rival theoretical positions.

The most compelling evidence for Epstein et al.'s central thesis that adult second language acquisition is constrained by the innate cognitive structures that constrain native language acquisition would be evidence of poverty of the stimulus. Although there are studies that point to such evidence, Epstein et al.'s primary form of argumentation, targetlike performance by second-language acquiring adults, is much less convincing.

Neurobiological models of language need a level of analysis that can account for the typical range of language phenomena. Because linguistically motivated models have been successful in explaining numerous language properties, it is premature to dismiss them as biologically irrelevant. Models attempting to unify neurobiology and linguistics need to be sensitive to both sources of evidence.

Contrary to Müller's claims, and in support of modular theories, genetic factors play a substantial and significant role in language. The finding that some children with specific language impairment (SLI) have nonlinguistic impairments may reflect improper diagnosis of SLI or impairments that are secondary to linguistic impairments. Thus, such findings do not argue against the modularity thesis. The lexical/functional distinction appears to be innate and specifically linguistic and could be instantiated in either symbolic or connectionist systems.

Müller argues that general cognitive skills and linguistic skills are not necessarily independent. However, cross-linguistic evidence from an inherited specific language disorder affecting productive rules suggests significant degrees of modularity, innateness, and universality of language. Confident claims about the overall nature of such a complex system still await more interdisciplinary research.

I enlarge on the theme that the brain mechanisms required for languageand other aspects of the human mind evolved through selective changes in the regulatory genes governing growth. Extension of the period of postnatal growth increases the role of the environment in structuring the brain, and spatiotemporal programming (heterochrony) ofgrowth might explain hierarchical representation, hemispheric specialization, and perhaps sex differences.

The study of signed languages has inspired scientific' speculation regarding foundations of human language. Relationships between the acquisition of sign language in apes and man are discounted on logical grounds. Evidence from the differential hreakdown of sign language and manual pantomime places limits on the degree of overlap between language and nonlanguage motor systems. Evidence from functional magnetic resonance imaging reveals neural areas of convergence and divergence underlying signed and spoken languages.

Both autonomy and local specificity are compatible with observed interconnectivity at the cell level when considering two different levels: cell assemblies and brain systems. Early syntactic structuring processes in particular are likely to representan autonomous module in the language/brain system.

Three issues are addressed in this commentary. (1) Wilkins & Wakefield are commended for placing the complex behavior they discuss within an evolutionary matrix. (2) They err on a number of points in regard to their treatment of this complex behavior. These involve (a) their emphasis on the evolution of conceptual structure rather than language, (b) their equation of meaning with reference, (c) their minimalist view of learning theory, and (d) their separation of the evolution of speech from that of (...) language. (3) They adopt a framework for neural preconditions that has been clearly discredited on both behavioral and neuroanatomical grounds. Finally, recent research involving modern neuroimaging techniques casts further doubt on the authors' postulated functions for the neural areas they discuss. (shrink)

Wilkins & Wakefield fall short of solving the language origin puzzle because they underestimate the cognitive and linguistic capacities of great apes. A focus on ape capacities leads to the recognition of varied levels of cognition and language and to a gradualistic model of language emergence in which early hominid language skills exceed those of the apes but fall far short of those of modern humans or later fossil hominid groups.

This target article presents a plausible evolutionary scenario for the emergence of the neural preconditions for language in the hominid lineage. In pleistocene primate lineages there was a paired evolutionary expansion of frontal and parietal neocortex (through certain well-documented adaptive changes associated with manipulative behaviors) resulting, in ancestral hominids, in an incipient Broca's region and in a configurationally unique junction of the parietal, occipital, and temporal lobes of the brain (the POT). On our view, the development of the POT in (...) our ancestors resulted in the neuroanatomical substrate consistent with the ability for representations in modality-neutral association cortex and, as a result of structure-imposing interaction with Broca's area, the hierarchically structured Evidence from paleoneurology and comparative primate neuroanatomy is used to argue that Homo habilis (2.5–2 million years ago) was the first hominid to have the appropriate gross neuroanatomical configuration to support conceptual structure. We thus suggest that the neural preconditions for language are met in H. habilis. Finally, we advocate a theory of language acquisition that uses conceptual structure as input to the learning procedures, thus bridging the gap between it and language. (shrink)

Critics of the computational connectionism of the last decade suggest that it shares undesirable features with earlier empiricist or associationist approaches, and with behaviourist theories of learning. To assess the accuracy of this charge the works of earlier writers are examined for the presence of such features, and brief accounts of those found are given for Herbert Spencer, William James and the learning theorists Thorndike, Pavlov and Hull. The idea that cognition depends on associative connections among large networks of neurons (...) is indeed one with precedents, although the implications of this for psychological issues have been interpreted variously — not all versions of connectionism are alike. (shrink)

Evolutionary linguistics is methodologically inspired by evolutionary psychology and the neo-Darwinian, selectionist approach. Language is claimed to have evolved by means of natural selection. The focus therefore lies not on how language evolved, but on finding out why language evolved. This latter question is answered by identifying the functional benefits and adaptive status that language provides, from which in turn selective pressures are deduced. This article analyses five of the most commonly given pressures or reasons why presumably language evolved. I (...) demonstrate that these reasons depend on functional definitions of what language is. To undo this bias, I suggest that scholars move away from the ?why? and ?what for? questions of language evolution, and focus on how language actually evolved. The latter project inquires into the distinct evolutionary mechanisms enabling the evolution of the anatomical and sociocultural traits underlying linguistic behaviour. (shrink)

Recent research suggests that language evolution is a process of cultural change, in which linguistic structures are shaped through repeated cycles of learning and use by domain-general mechanisms. This paper draws out the implications of this viewpoint for understanding the problem of language acquisition, which is cast in a new, and much more tractable, form. In essence, the child faces a problem of induction, where the objective is to coordinate with others (C-induction), rather than to model the structure of the (...) natural world (N-induction). We argue that, of the two, C-induction is dramatically easier. More broadly, we argue that understanding the acquisition of any cultural form, whether linguistic or otherwise, during development, requires considering the corresponding question of how that cultural form arose through processes of cultural evolution. This perspective helps resolve the “logical” problem of language acquisition and has far-reaching implications for evolutionary psychology. (shrink)

How do minds emerge from developing brains? According to the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: minimizes the need for prespecification in accordance with recent neurobiological evidence (...) that the developing cerebral cortex is largely free of domain-specific structure. Instead, the representational properties of cortex are built by the nature of the problem domain confronting it. This uniquely powerful and general learning strategy undermines the central assumption of classical learnability theory, that the learning properties of a system can be deduced from a fixed computational architecture. Neural constructivism suggests that the evolutionary emergence of neocortex in mammals is a progression toward more flexible representational structures, in contrast to the popular view of cortical evolution as an increase in innate, specialized circuits. Human cortical postnatal development is also more extensive and protracted than generally supposed, suggesting that cortex has evolved so as to maximize the capacity of environmental structure to shape its structure and function through constructive learning. (shrink)

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes of language change (...) are much more rapid than processes of genetic change, language constitutes a both over time and across different human populations, and, hence, cannot provide a stable environment to which language genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent which evolves under selectional pressures from human learning and processing mechanisms. That is, languages themselves are shaped by severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases deriving from the structure of thought processes, perceptuo-motor factors, cognitive limitations, and pragmatics. (shrink)

Current approaches to mathematical cognition divide into two major camps. Cognitive studies try to render mathematical intuition—the faculty that gives us immediate and authoritative knowledge of mathematics—respectable on scientific grounds. Cultural studies, on the other hand, regard mathematics as a form of cultural achievement, like literature or architecture. Both positions have their own shortcomings. While cognitive approaches are limited in scope and fail to account for complex mathematical developments, cultural approaches are short of detailed answers as to what enables us (...) to participate in a common mathematical practice. This situation evinces a need to balance a cognitive perspective on mathematical culture against a cultural perspective on mathematical cognition. According to current behavioral and neuropsychological evidence, the complex, uniquely human, culture-specific mathematical skills exhibited by human adults rest on a set of psychological and neural mechanisms that (a) are shared by other animals, and (b) emerge early in human development, continue to function throughout the lifespan, and thus are common to infants, children and adults. It has been proposed that these common and evolutionary ancient mechanisms account for humans’ basic “number sense” and form the building blocks for the development of more sophisticated numerical skills. Indeed, infants leave animals far behind in their numerical sophistication. What boosts this developmental difference? How do human beings acquire mathematical concepts such as the concept of natural number? First, I specify the representations that are the building blocks for the target concepts. Second, I describe how the target concepts differ from these basic representations. And finally, I characterize the learning mechanisms that enable the construction of the target concepts out of those prior representations. I argue that the power of the resulting conceptual system derives from the combination and integration of previously distinct representational systems, capitalizing on the human capacity for creating and using external symbols: human beings can only develop their distinct conceptual abilities due to their original embeddedness in both the physical world and, most importantly, in a rich milieu of cultural resources. Thus, an important developmental source of number representations, in addition to the preverbal systems mentioned above, is the representation of numbers within natural language. (shrink)

This thesis aims to develop a psychologically plausible account of concepts by integrating key insights from philosophy (on the metaphysical basis for concept possession) and psychology (on the mechanisms underlying concept acquisition). I adopt an approach known as informational atomism, developed by Jerry Fodor. Informational atomism is the conjunction of two theses: (i) informational semantics, according to which conceptual content is constituted exhaustively by nomological mind–world relations; and (ii) conceptual atomism, according to which (lexical) concepts have no internal structure. I (...) argue that informational semantics needs to be supplemented by allowing content-constitutive rules of inference (“meaning postulates”). This is because the content of one important class of concepts, the logical terms, is not plausibly informational. And since, it is argued, no principled distinction can be drawn between logical concepts and the rest, the problem that this raises is a general one. An immediate difficulty is that Quine’s classic arguments against the analytic/synthetic distinction suggest that there can be no principled basis for distinguishing content-constitutive rules from the rest. I show that this concern can be overcome by taking a psychological approach: there is a fact of the matter as to whether or not a particular inference is governed by a mentally-represented inference rule, albeit one that analytic philosophy does not have the resources to determine. I then consider the implications of this approach for concept acquisition. One mechanism underlying concept acquisition is the development of perceptual detectors for the objects that we encounter. I investigate how this might work, by drawing on recent ideas in ethology on ‘learning instincts’, and recent insights into the neurological basis for perceptual learning. What emerges is a view of concept acquisition as involving a complex interplay between innate constraints and environmental input. This supports Fodor’s recent move away from radical concept nativism: concept acquisition requires innate mechanisms, but does not require that concepts themselves be innate. (shrink)

We focus on Karmiloff-Smith's Representational redescription model, arguing that it poses some problems concerning the architecture of a redescribing system. To discuss the topic, we consider the implicit/explicit dichotomy and the relations between natur al language and the language of thought. We argue that the model regards how knowledge is employed rather than how it is represented in the system.

Some opponents of the incommensurability thesis, such as Davidson and Rorty, have argued that the very idea of incommensurability is incoherent and that the existence of alternative and incommensurable conceptual schemes is a conceptual impossibility. If true, this refutes Kuhnian relativism and Kantian scepticism in one fell swoop. For Kuhnian relativism depends on the possibility of alternative, humanly accessible conceptual schemes that are incommensurable with one another, and the Kantian notion of a realm of unknowable things-in-themselves gives rise to the (...) possibility of humanly inaccessible schemes that are incommensurable with even our best current or future science. In what follows we argue that the possibility of incommensurability of either the Kuhnian or the Kantian variety is inescapable and that this conclusion is forced upon us by a simple consideration of what is involved in acquiring a concept. It turns out that the threats from relativism and scepticism are real, and that anyone, including Davidson himself, who has ever defended an account of concept acquisition is committed to one or the other of these two possibilities.1. (shrink)

The number of studies related to natural and artificial mechanisms of learning rapidly increases. However, there is no general theory of learning that could provide a unifying basis for exploring different directions in this growing field. For a long time the development of such a theory has been hindered by nativists' belief that the development of a biological organism during ontogeny should be viewed as parameterization of an innate, encoded in the genome structure by an innate algorithm, and nothing essentially (...) new is created during this process. Noam Chomsky has claimed, therefore, that the creation of a non-trivial general mathematical theory of learning is not feasible, since any algorithm cannot produce a more complex algorithm. This study refutes the above argumentation by developing a counter-example based on the mathematical theory of algorithms and computable functions. It introduces a novel concept of a Universal Learning System (ULS) capable of learning to control in an optimal way any given constructive system from a certain class. The necessary conditions for the existence of a ULS and its main functional properties are investigated. The impossibility of building an algorithmic ULS for a sufficiently complex class of controlled objects is shown, and a proof of the existence of a non-algorithmic ULS based on the axioms of classical mathematics is presented. It is argued that a non-algorithmic ULS is a legitimate object of not only mathematics, but also the world of nature. These results indicate that an algorithmic description of the organization and adaptive development of biological systems in general is not sufficient. At the same time, it is possible to create a rigorous non-algorithmic general theory of learning as a theory of ULS. The utilization of this framework for integrating learning-related studies is discussed. (shrink)

Many people have argued that the evolution of the human language faculty cannot be explained by Darwinian natural selection. Chomsky and Gould have suggested that language may have evolved as the by-product of selection for other abilities or as a consequence of as-yet unknown laws of growth and form. Others have argued that a biological specialization for grammar is incompatible with every tenet of Darwinian theory – that it shows no genetic variation, could not exist in any intermediate forms, confers (...) no selective advantage, and would require more evolutionary time and genomic space than is available. We examine these arguments and show that they depend on inaccurate assumptions about biology or language or both. Evolutionary theory offers clear criteria for when a trait should be attributed to natural selection: complex design for some function, and the absence of alternative processes capable of explaining such complexity. Human language meets these criteria: Grammar is a complex mechanism tailored to the transmission of propositional structures through a serial interface. Autonomous and arbitrary grammatical phenomena have been offered as counterexamples to the position that language is an adaptation, but this reasoning is unsound: Communication protocols depend on arbitrary conventions that are adaptive as long as they are shared. Consequently, language acquisition in the child should systematically differ from language evolution in the species, and attempts to analogize them are misleading. Reviewing other arguments and data, we conclude that there is every reason to believe that a specialization for grammar evolved by a conventional neo-Darwinian process. (shrink)

In recent times evolutionary psychologists have offered adaptation explanations for a wide range of human psychological characteristics. Critics, however, have argued that such endeavors are problematic because the appropriate evidence required to demonstrate adaptation is unlikely to be forthcoming, therefore severely limiting the role of the adaptationist program in psychology. More specifically, doubts have been raised over both the methodology employed by evolutionary psychologists for studying adaptations and about the possibility of ever developing acceptably rigorous evolutionary explanations of human psychological (...) phenomena. We argue that by employing a wide range of methods for inferring adaptation and by adopting an inference to the best explanation strategy for evaluating adaptation explanations, these two doubts can be adequately addressed. We illustrate how this approach can be fruitfully employed in evaluating claims about the evolutionary origins of language, and conclude with a brief discussion of the future of evolutionary psychology. (shrink)

The philosophical innateness debate has long relied onpsychological evidence. For a century, however, a parallel debate hastaken place within neuroscience. In this paper, I consider theimplications of this neuroscience debate for the philosophicalinnateness debate. By combining the tools of theoretical neurobiologyand learning theory, I introduce the ``problem of development'' that alladaptive systems must solve, and suggest how responses to this problemcan demarcate a number of innateness proposals. From this perspective, Isuggest that the majority of natural systems are in fact innate. (...) Lastly,I consider the acquistion strategies implemented by the human brain andsuggest that there is a rigorous way of characterizing these ``neuralconstructivist'' strategies as not being strongly innate. Alternatives toinnateness are thus both rigorously definable and empirically supported. (shrink)

Certain of our concepts are innate, but many others are learned. Despite the plausibility of this claim, some have argued that the very idea of concept learning is incoherent. I present a conception of learning that sidesteps the arguments against the possibility of concept learning, and sketch several mechanisms that result in the generation of new primitive concepts. Given the rational considerations that motivate their deployment, I argue that these deserve to be called learning mechanisms. I conclude by replying to (...) the objections that these mechanisms cannot produce genuinely new content and cannot be part of genuinely cognitive explanations. (shrink)

The Darwinian theory of evolution is itself evolving and this book presents the details of the core of modern Darwinism and its latest developmental directions. The authors present current scientific work addressing theoretical problems and challenges in four sections, beginning with the concepts of evolution theory, its processes of variation, heredity, selection, adaptation and function, and its patterns of character, species, descent and life. The second part of this book scrutinizes Darwinism in the philosophy of science and its usefulness in (...) understanding ecosystems, whilst the third section deals with its application in disciplines beyond the biological sciences, including evolutionary psychology and evolutionary economics, Darwinian morality and phylolinguistics. The final section addresses anti-Darwinism, the creationist view and issues around teaching evolution in secondary schools. The reader learns how current experimental biology is opening important perspectives on the sources of variation, and thus of the very power of natural selection. This work examines numerous examples of the extension of the principle of natural selection and provides the opportunity to critically reflect on a rich theory, on the methodological rigour that presides in its extensions and exportations, and on the necessity to measure its advantages and also its limits. Scholars interested in modern Darwinism and scientific research, its concepts, research programs and controversies will find this book an excellent read, and those considering how Darwinism might evolve, how it can apply to the human sciences and other disciplines beyond its origins will find it particularly valuable. Originally produced in French (Les Mondes Darwiniens), the scope and usefulness of the book have led to the production of this English text, to reach a wider audience. This book is a milestone in the impressive penetration by Francophone scholars into the world of Darwinian science, its historiography and philosophy over the last two decades. Alex Rosenberg, R. Taylor Cole Professor of Philosophy, Duke University Until now this useful and comprehensive handbook has only been available to francophones. Thanks to this invaluable new translation, this collection of insightful and original essays can reach the global audience it deserves. Tim Lewens, University of Cambridge. (shrink)

Discussions about the extended mind have ‘extended’ in various directions in the last decades. While applied to other aspects of human cognition and even consciousness, the extended-mind hypothesis has also been criticized, as it questions fundamental ideas such as the image of a dual world, divided between an external and an internal domain by the border of ‘skin and skull’, the idea of a localized and constant decision center, and the role of internal representations. We suggest that the main virtue (...) of the hypothesis is not as a theory per se, but as a vaccine against persistent metaphysical prejudices about the mind’s structure, functions and borders. Being an hypothesis about the most efficient ways to combine resources and problems, and not a theory about the mind’s a-priori constitution, the extended mind view moves the focus from ontology to pragmatics and helps purify philosophy of mind from metaphysical remainders. (shrink)

Following the development of the selectionist theory of the immune system, there was an attempt to characterise many biological mechanisms as being ‘selectionist’ as juxtaposed with ‘instructionist’. However, this broad definition would group Darwinian evolution, the immune system, embryonic development, and Chomsky’s principles-and-parameters language-acquisition mechanism together under the ‘selectionist’ umbrella, even though Chomsky’s mechanism and embryonic development are significantly different from the selectionist mechanisms of biological evolution and the immune system. Surprisingly, there is an abstract way using two dual mathematical (...) logics to make the distinction between genuinely selectionist mechanisms and what are better called ‘generative’ or symmetry-breaking mechanisms. This distinction is outlined in this note. (shrink)

Modularity has been the subject of intense debate in the cognitive sciences for more than 2 decades. In some cases, misunderstandings have impeded conceptual progress. Here the authors identify arguments about modularity that either have been abandoned or were never held by proponents of modular views of the mind. The authors review arguments that purport to undermine modularity, with particular attention on cognitive architecture, development, genetics, and evolution. The authors propose that modularity, cleanly defined, provides a useful framework for directing (...) research and resolving debates about individual cognitive systems and the nature of human evolved cognition. Modularity is a fundamental property of living things at every level of organization; it might prove indispensable for understanding the structure of the mind as well. (shrink)