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.

Müller attempts to downplay cases of dissociation between language and cognition as evidence against the modularity of language. We review cases of associations between verbal and nonverbal abilities as further evidence against the notion of language as an autonomous subsystem. We also point out a discrepancy between his proposal of homologies between nonhuman primates' communication and human language and recent proposals on the evolution of language.

David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science . Thus, by focusing on levels of description, one can sharpen foundational differences between (...) classicism and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)

What counts as a computation and how it relates to cognitive function are important questions for scientists interested in understanding how the mind thinks. This paper argues that pragmatic aspects of explanation ultimately determine how we answer those questions by examining what is needed to make rigorous the notion of computation used in the (cognitive) sciences. It (1) outlines the connection between the Church-Turing Thesis and computational theories of physical systems, (2) differentiates merely satisfying a computational function from true computation, (...) and finally (3) relates how we determine a true computation to the functional methodology in cognitive science. All of the discussion will be directed toward showing that the only way to connect formal notions of computation to empirical theory will be in virtue of the pragmatic aspects of explanation. (shrink)

This is an amended version of material that first appeared in A. Clark, Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing (MIT Press, Cambridge, MA, 1989), Ch. 1, 2, and 6. It appears in German translation in Metzinger,T (Ed) DAS LEIB-SEELE-PROBLEM IN DER ZWEITEN HELFTE DES 20 JAHRHUNDERTS (Frankfurt am Main: Suhrkamp. 1999).

This paper argues that the faculty of language comes essentially for free in evolutionary terms, by grace of a capacity shared with some evolutionarily quite distantly related animals for deliberatively planning action in the world. The reason humans have language of a kind that animals do not is because of a qualitative difference in the nature of human plans rather than anything unique to language.

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.

Müller argues that double dissociations do not imply underlying modularity of the cognitive system, citing neural networks as examples of fully distributed systems that can give rise to double dissociations. We challenge this claim, noting that suchdouble dissociations typically do not “scale-up,” and that even some singledissociations can be difficult to account for in a distributed system.

In this paper I defend the classical computational account of reasoning against a range of highly influential objections, sometimes called relevance problems. Such problems are closely associated with the frame problem in artificial intelligence and, to a first approximation, concern the issue of how humans are able to determine which of a range of representations are relevant to the performance of a given cognitive task. Though many critics maintain that the nature and existence of such problems provide grounds for rejecting (...) classical computationalism, I show that this is not so. Some of these putative problems are a cause for concern only on highly implausible assumptions about the extent of our cognitive capacities, whilst others are a cause for concern only on similarly implausible views about the commitments of classical computationalism. Finally, some versions of the relevance problem are not really objections but hard research issues that any satisfactory account of cognition needs to address. I conclude by considering the diagnostic issue of why accounts of cognition in general—and classical computational accounts, in particular—have faired so poorly in addressing such research issues.Keywords: Computationalism; Frame problem; Relevance. (shrink)

In the study of cognitive processes, limitations on computational resources (computing time and memory space) are usually considered to be beyond the scope of a theory of competence, and to be exclusively relevant to the study of performance. Starting from considerations derived from the theory of computational complexity, in this paper I argue that there are good reasons for claiming that some aspects of resource limitations pertain to the domain of a theory of competence.

David Marr provided an influential account of levels of description in classical cognitive science. In this paper we contrast Marr'ent with some alternatives that are suggested by the recent emergence of connectionism. Marr's account is interesting and important both because of the levels of description it distinguishes, and because of the way his presentation reflects some of the most basic, foundational, assumptions of classical AI-style cognitive science. Thus, by focusing on levels of description, one can sharpen foundational differences between classicism (...) and potential non-classical conceptions of mentality that might emerge under the rubric of connectionism. (shrink)

Recent work in the methodology of connectionist explanation has I'ocrrsccl on the notion of levels of explanation. Specific issucs in conncctionisrn hcrc intersect with rvider areas of debate in the philosophy of psychology and thc philosophy of science generally. The issues I raise in this chapter, then, are not unique to cognitive science; but they arise in new and important contexts when connectionism is taken seriously as a model of cognition. The general questions are the relation between levels and the (...) status of levels which have no obvious relation to others. In speaking of levels, what is the connection, if there is one, between explanation and ontology? Which, if any, conccpt of reduction is applicable to connectionist systems? What kind of legitinrtcy can the constructs of common sense psychology, or of that vclsion ol intentional realism represented by classical symbol-systems n I, hirvc irr ir full-scale connectionist theory of mind? (shrink)

This article compares the potential of classical and connectionist computational concepts for explanations of innate infant knowledge and of its development. It focuses on issues relating to: the perceptual process; the control and form(s) of perceptual-behavioural coordination; the role of environmental structure in the organization of action; and the construction of novel forms of activity. There is significant compatibility between connectionist and classical views of computation, though classical concepts are, at present, better able to provide a comprehensive computational view of (...) the infant. However, Varela's “enaction” perspective poses a significant challenge for both approaches. (shrink)

This paper discusses some requirements on a folk-psychological, computational account of concepts. Although most psychological views take the folk-psychological stance that concept-possession requires capacities of both representation and classification, such views lack a philosophical context. In contrast, philosophically motivated views stress one of these capacities at the expense of the other. This paper seeks to provide some philosophical motivation for the (folk-) psychological stance. Philosophical and psychological constraints on a computational level account provide the context for evaluating two theses. The (...) first, the Classificatory View, is that concept-possession is constituted by the ability to classify states of the world. I argue, against this view, that to be able to classify, a thinker must also be able to represent the world. The second thesis, the Representational View, is that to possess a concept is constituted by the ability to represent the world. I argue that ascribing this ability is incoherent without ascribing an ability to classify. Hence, a detailed computational specification of concept-possession suggests that the folk-psychological stance is accurate. Philosophical views of concepts, (e.g. Fodor, 1987), adhering to one of the strong theses, whilst adverting to folk-psychological motivations, are thus both insufficiently complex and incoherent. (shrink)