In Minimal Rationality, Christopher Cherniak boldly challenges the myth of Man the the Rational Animal and the central role that the "perfectly rational...

Jerry Fodor argues against the widely held view that mental processes are largely computations, that the architecture of cognition is massively modular, and...

This paper sketches a solution to a problem which has been emphasized by Fodor. This is the problem of how to explain distinctively-human flexible cognition in modular terms. There are three aspects to the proposed account. First, it is suggested that natural language sentences might serve to integrate the outputs of a number of conceptual modules. Second, a creative sentence-generator, or supposer, is postulated. And third, it is argued that a set of principles of inference to the best explanation can (...) be constructed from already-extant aspects of linguistic testimony and discourse interpretation. Most importantly, it is suggested that the resulting architecture should be implementable in ways that are computationally tractable. (shrink)

Newton's bucket, Einstein's elevator, Schrödinger's cat – these are some of the best-known examples of thought experiments in the natural sciences. But what function do these experiments perform? Are they really experiments at all? Can they help us gain a greater understanding of the natural world? How is it possible that we can learn new things just by thinking? In this revised and updated new edition of his classic text _The Laboratory of the Mind_, James Robert Brown continues to defend (...) apriorism in the physical world. This edition features two new chapters, one on “counter thought experiments” and another on the development of inertial motion. With plenty of illustrations and updated coverage of the debate between Platonic rationalism and classic empiricism, this is a lively and engaging contribution to the field of philosophy of science. (shrink)

Harman distinguishes between two uses of the term “logic”: as referring either to the theory of implication or to the theory of reasoning, which are quite distinct. His interest here is reasoning: a process that can modify intentions and beliefs. To a first approximation, theoretical reasoning is concerned with what to believe and practical reasoning is concerned with what to intend to do, although it is possible to have practical reasons to believe something. Practical considerations are relevant to whether to (...) engage in theoretical inquiry into a given question, the extent of time and other resources to devote to such inquiry, and whether and when to end such inquiry. Simplicity and conservatism play a role in theoretical reasoning that can be given a practical justification without allowing wishful thinking into theoretical reasoning, a justification that can also be given a non-practical interpretation. (shrink)

The frame problem was originally a problem for Artificial Intelligence, but philosophers have interpreted it as an epistemological problem for human cognition. As a result of this reinterpretation, however, specifying the frame problem has become a difficult task. To get a better idea of what the frame problem is, how it gives rise to more general problems of relevance, and how deep these problems run, I expound six guises of the frame problem. I then assess some proposed heuristic solutions to (...) the frame problem; I show that these proposals misunderstand, and fail to address, an important aspect of the frame problem. Finally, I argue that though human cognition does not solve the frame problem in its epistemological guise, human cognition avoids some of the epistemological worries. (shrink)

Modern empiricism has been conditioned in large part by two dogmas. One is a belief in some fundamental cleavage between truths which are analytic, or grounded in meanings independently of matters of fact, and truth which are synthetic, or grounded in fact. The other dogma is reductionism: the belief that each meaningful statement is equivalent to some logical construct upon terms which refer to immediate experience. Both dogmas, I shall argue, are ill founded. One effect of abandoning them is, as (...) we shall see, a blurring of the supposed boundary between speculative metaphysics and natural science. Another effect is a shift toward pragmatism. (shrink)

This revised edition includes a new Preface outlining developments in Relevance Theory since 1986, discussing the more serious criticisms of the theory, and ...

`Folk Psychology' - our everyday talk of beliefs, desires and mental events - has long been compared with the technical language of `Cognitive Science'. Does folk psychology provide a correct account of the mental causes of our behaviour, or must our everyday terms ultimately be replaced by a language developed from computational models and neurobiology? This broad-ranging book addresses these questions, which lie at the heart of psychology and philosophy. Providing a critical overview of the key literature in the field, (...) including the seminal work of Fodor and Churchland, the author explores the classic `Frame Problem' and assesses the future prospects of cognitive science. The scope of the frame problem, touching on connec. (shrink)

In my book How the Mind Works, I defended the theory that the human mind is a naturally selected system of organs of computation. Jerry Fodor claims that 'the mind doesn't work that way'(in a book with that title) because (1) Turing Machines cannot duplicate humans' ability to perform abduction (inference to the best explanation); (2) though a massively modular system could succeed at abduction, such a system is implausible on other grounds; and (3) evolution adds nothing to our understanding (...) of the mind. In this review I show that these arguments are flawed. First, my claim that the mind is a computational system is different from the claim Fodor attacks (that the mind has the architecture of a Turing Machine); therefore the practical limitations of Turing Machines are irrelevant. Second, Fodor identifies abduction with the cumulative accomplishments of the scientific community over millennia. This is very different from the accomplishments of human common sense, so the supposed gap between human cognition and computational models may be illusory. Third, my claim about biological specialization, as seen in organ systems, is distinct from Fodor's own notion of encapsulated modules, so the limitations of the latter are irrelevant. Fourth, Fodor's arguments dismissing of the relevance of evolution to psychology are unsound. (shrink)

The Modularity of Mind proposes an alternative to the or view of cognitive architecture that has dominated several decades of cognitive science. Whereas interactionism stresses the continuity of perceptual and cognitive processes, modularity theory argues for their distinctness. It is argued, in particular, that the apparent plausibility of New Look theorizing derives from the failure to distinguish between the (correct) claim that perceptual processes are inferential and the (dubious) claim that they are unencapsidated, that is, that they are arbitrarily sensitive (...) to the organism's beliefs and desires. In fact, according to modularity theory, perceptual processes are computationally isolated from much of the background knowledge to which cognitive processes have access. The postulation of autonomous, domain-specific psychological mechanisms underlying perceptual integration connects modularity theory with the tradition of faculty psychology, in particular, with the work of Franz Joseph Call. Some of these historical affinities, and some of the relations between faculty psychology and Cartesianism, are discussed in the book. (shrink)

How do novel scientific concepts arise? In Creating Scientific Concepts, Nancy Nersessian seeks to answer this central but virtually unasked question in the problem of conceptual change. She argues that the popular image of novel concepts and profound insight bursting forth in a blinding flash of inspiration is mistaken. Instead, novel concepts are shown to arise out of the interplay of three factors: an attempt to solve specific problems; the use of conceptual, analytical, and material resources provided by the cognitive-social-cultural (...) context of the problem; and dynamic processes of reasoning that extend ordinary cognition. Focusing on the third factor, Nersessian draws on cognitive science research and historical accounts of scientific practices to show how scientific and ordinary cognition lie on a continuum, and how problem-solving practices in one illuminate practices in the other. (shrink)

Do accounts of scientific theory formation and revision have implications for theories of everyday cognition? We maintain that failing to distinguish between importantly different types of theories of scientific inference has led to fundamental misunderstandings of the relationship between science and everyday cognition. In this article, we focus on one influential manifestation of this phenomenon which is found in Fodor's well-known critique of theories of cognitive architecture. We argue that in developing his critique, Fodor confounds a variety of distinct claims (...) about the holistic nature of scientific inference. Having done so, we outline more promising relations that hold between theories of scientific inference and ordinary cognition. (shrink)

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)

This chapter examines the scope and limits of the tractability argument. It argues for two claims. First, that when explored with appropriate care and attention, it becomes clear that the argument provides no good reason to prefer massive modularity to the more traditional rationalist alternative. Second, while it is denied that tractability considerations support massive modularity per se, this does not mean that they show nothing whatsoever. Careful analysis of tractability considerations suggests a range of characteristics that any plausible version (...) of psychological rationalism is likely to possess. The chapter proceeds as follows: Section 1 outlines and clarifies the general form of the tractability argument. Section 2 explains how massive modularity is supposed to resolve intractability worries. Sections 3 to 7 highlight the deficiencies of the main extant arguments for claiming that nonmodular mechanisms are intractable. Section 8 concludes by sketching some of the general characteristics that a plausible rationalist alternative to massive modularity — one capable of subserving tractable cognitive processes — is likely to possess. (shrink)

I present the symbol grounding problem in the larger context of a materialist theory of content and then present two problems for causal, teleo-functional accounts of content. This leads to a distinction between two kinds of mental representations: presentations and symbols; only the latter are cognitive. Based on Milner and Goodale’s dual route model of vision, I posit the existence of precise interfaces between cognitive systems that are activated during object recognition. Interfaces are constructed as a child learns, and is (...) taught, how to interact with its environment; hence, interface structure has a social determinant essential for symbol grounding. Symbols are encoded in the brain to exploit these interfaces, by having projections to the interfaces that are activated by what they symbolise. I conclude by situating my proposal in the context of Harnad’s (1990) solution to the symbol grounding problem and responding to three standard objections. (shrink)

Jerry Fodor has argued that a modular mind must include central systems responsible for updating beliefs, and has defended this position by appealing to shared properties of belief fixation and scientific confirmation. Peter Carruthers and Stephen Pinker have attacked this analogy between science and ordinary inference. I examine their arguments and show that they fail. This does not show that Fodor’s more general position is correct.