This paper deals with two opposite metaphilosophical doctrines concerning the nature of philosophy. More specifically, it is a study of the naturalistic view that philosophical, hence also epistemological, knowledge cannot be distinguished from empirical knowledge, and of the antinaturalistic view that philosophical, hence also epistemological, knowledge, is pure, that is, independent of empirical knowledge and particularly of the special sciences. The conditions of the possibility of naturalistic and of pure epistemology are studied in terms of phenomenological philosophy. It is concluded (...) that pure epistemology is possible under relatively strong conditions but that the version of naturalistic epistemology which denies the pure basis leads to contradiction. That, however, does not shake the possibility of cognitive science. Following Husserl, we may argue that studies of human cognition are possible on the condition that a first basis is assumed which is not naturalized. (shrink)

While purely causal theories of reference have provided a plausible account of the meanings of names and natural kind terms, they cannot handle vacuous theoretical terms. The causal homeostasis theory can but incurs other difficulties. Theories of reference that are intensional and not purely causal tend to be molecularist or holist. Holist theories threaten transtheoretic reference, whereas molecularist theories must supply a principled basis for selecting privileged meaning-determining relations between terms. The causal homeostasis theory is a two-factor molecularist theory, but (...) it fails to provide such a principled basis and collapses into holism. A naturalistic, non-foundationalist holism that deploys strategies of intertheoretic reduction and co-evolutionary pluralism can, however, yield a credible version of transtheoretic reference. (shrink)

There is widespread belief that connectionist networks are dramatically different from classical or symbolic models. However, connectionists rarely test this belief by interpreting the internal structure of their nets. A new approach to interpreting networks was recently introduced by Berkeley et al. (1995). The current paper examines two implications of applying this method: (1) that the internal structure of a connectionist network can have a very classical appearance, and (2) that this interpretation can provide a cognitive theory that cannot be (...) dismissed as a mere implementation. (shrink)

Embedded and embodied approaches to cognition urge that (1) complicated internal representations may be avoided by letting features of the environment drive behavior, and (2) environmental structures can play an enabling role in cognition, allowing prior cognitive processes to solve novel tasks. Such approaches are thus in a natural position to oppose the ‘thesis of linguistic structuring’: The claim that the ability to use language results in a wholesale recapitulation of linguistic structure in onboard mental representation. Prominent examples of researchers (...) adopting this critical stance include Andy Clark, Michael Wheeler, and Mark Rowlands. But is such opposition warranted? Since each of these authors advocate accounts of mental representation that are broadly connectionist, I survey research on formal language computation in artificial neural networks, and argue that results indicate a strong form of the linguistic structuring thesis is true: Internal representational systems recapitulate significant linguistic structure, even on a connectionist account of mental representation. I conclude by sketching how my conclusion can nonetheless be viewed as consistent with and complimentary to an embedded/embodied account of the role of linguistic structure in cognition. (shrink)

Many of the mathematicians and scientists who guided the development of digital computers in the late 1940s, such as Alan Turing and John von Neumann, saw these new devices not just as tools for calculation but as devices that might employ the same principles as are exhibited in rational human thought. Thus, a subfield of what came to be called computer science assumed the label artificial intelligence. The idea of building artificial systems which could exhibit intelligent behavior comparable to that (...) of humans was a heady prospect, and the claims made on behalf of AI during the 1950s and 1960s were impossibly ambitious. Despite some theoretical and applied successes within the field, serious problems soon became evident. Instead of fulfilling the goal of quickly producing artificial intelligent agents which could compete with or outperform human beings, by the 1970s and 1980s AI had settled into a pattern of slower but real progress in modeling or simulating aspects of human intelligence. (shrink)

Many studies of language, whether in philosophy, linguistics, or psychology, have focused on highly developed human languages. In their highly developed forms, such as are employed in scientific discourse, languages have a unique set of properties that have been the focus of much attention. For example, descriptive sentences in a language have the property of being "true" or "false," and words of a language have senses and referents. Sentences in a language are structured in accord with complex syntactic rules. Theorists (...) focusing on language are naturally led to ask questions such as what constitutes the meanings of words and sentences and how are the principles of syntax encoded in the heads of language users. While there is an important function for inquiries into the highly developed forms of these cultural products (Abrahamsen, 1987), such a focus can be quite misleading when we want to explain how these products have arisen or the human capacity to use language. The problem is that focusing on its most developed forms makes linguistic ability seem to be a _sui generis_ phenomenon, not related to, and hence not explicable in terms of other cognitive capacities. Chomsky's (1980) postulation of a specific language module equipped with specialized resources needed to process language and possessed only by hum ans is not a surprising result. (shrink)

First paragraph: When we perform bodily gestures, are we ever literally thinking with our hands (arms, shoulders, etc.)? In the more precise, but correspondingly drier, technical language of contemporary philosophy of mind and cognition, essentially the same question might be asked as follows: are bodily gestures ever among the material vehicles that realize cognitive processes? More precisely still, is it ever true that a coupled system made up of neural activity and bodily gestures counts as realizing a process of thought, (...) in such a way that the gross bodily movements concerned should be granted cognitive status along with, and in essentially the same sense as, the neural activity? (shrink)

Horgan and Tienson do a wonderful job of explicating the dynamical system perspective and contrasting that view with classical AI approaches. However, their arguments for replacing a classical conception of connectionism with system dynamics rely on philosophical distinctions that do not make a difference. In particular, (1) their generalized version of Man's three levels of analysis collapses into itself; (2) their description of attractor dynamics works better than their metaphor of forces; and (3) their versions of “soft laws” and physical (...) laws amount to the same thing. (shrink)