We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...) construct new causal maps and that their learning is consistent with the Bayes net formalism. (shrink)

First, a brief historical trace of the developments in confirmation theory leading up to Goodman's infamous "grue" paradox is presented. Then, Goodman's argument is analyzed from both Hempelian and Bayesian perspectives. A guiding analogy is drawn between certain arguments against classical deductive logic, and Goodman's "grue" argument against classical inductive logic. The upshot of this analogy is that the "New Riddle" is not as vexing as many commentators have claimed. Specifically, the analogy reveals an intimate connection between Goodman's problem, and (...) the "problem of old evidence". Several other novel aspects of Goodman's argument are also discussed. (shrink)

This book explores the idea that much of our behaviour is controlled by automatic and intuitive mental processes, which shape and compete with our conscious thinking and decision making. Accessibly written, and assuming no prior knowledge of the field, the book will be fascinating reading for all those interested in human behaviour.

'Working Memory, Thought, and Action' is the magnum opus of one of the most influential cognitive psychologists of the past 50 years. This new volume on the model he created discusses the developments that have occurred within the model in the past twenty years, and places it within a broader context.

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)

Jerry Fodor presents a new development of his famous Language of Thought hypothesis, which has since the 1970s been at the centre of interdisciplinary debate about how the mind works. Fodor defends and extends the groundbreaking idea that thinking is couched in a symbolic system realized in the brain. This idea is central to the representational theory of mind which Fodor has established as a key reference point in modern philosophy, psychology, and cognitive science. The foundation stone of our present (...) cognitive science is Turing's suggestion that cognitive processes are not associations but computations; and computation requires a language of thought. So the latest on the Language of Thought hypothesis, from its progenitor, promises to be a landmark in the study of the mind. LOT 2 offers a more cogent presentation and a fuller explication of Fodor 's distinctive account of the mind, with various intriguing new features. The central role of compositionality in the representational theory of mind is revealed: most of what we know about concepts follows from the compositionality of thoughts. Fodor shows the necessity of a referentialist account of the content of intentional states, and of an atomistic account of the individuation of concepts. Not least among the new developments is Fodor 's identification and persecution of pragmatism as the leading source of error in the study of the mind today. LOT 2 sees Fodor advance undaunted towards the ultimate goal of a theory of the cognitive mind, and in particular a theory of the intentionality of cognition. No one who works on the mind can ignore Fodor 's views, expressed in the coruscating and provocative style which has delighted and disconcerted countless readers over the years. (shrink)

It has often been suggested that people’s ordinary capacities for understanding the world make use of much the same methods one might find in a formal scientific investigation. A series of recent experimental results offer a challenge to this widely-held view, suggesting that people’s moral judgments can actually influence the intuitions they hold both in folk psychology and in causal cognition. The present target article distinguishes two basic approaches to explaining such effects. One approach would be to say that the (...) relevant competencies are entirely non-moral but that some additional factor (conversational pragmatics, performance error, etc.) then interferes and allows people’s moral judgments to affect their intuitions. Another approach would be to say that moral considerations truly do figure in workings of the competencies themselves. It is argued that the data available now favor the second of these approaches over the first. (shrink)

APA PsycNET abstract: This is the first volume of a two-volume work on Probability and Induction. Because the writer holds that probability logic is identical with inductive logic, this work is devoted to philosophical problems concerning the nature of probability and inductive reasoning. The author rejects a statistical frequency basis for probability in favor of a logical relation between two statements or propositions. Probability "is the degree of confirmation of a hypothesis (or conclusion) on the basis of some given evidence (...) (or premises)." Furthermore, all principles and theorems of inductive logic are analytic, and the entire system is to be constructed by means of symbolic logic and semantic methods. This means that the author confines himself to the formalistic procedures of word and symbol systems. The resulting sentence or language structures are presumed to separate off logic from all subjectivist or psychological elements. Despite the abstractionism, the claim is made that if an inductive probability system of logic can be constructed it will have its practical application in mathematical statistics, and in various sciences. 16-page bibliography. (PsycINFO Database Record (c) 2016 APA, all rights reserved). (shrink)

Attempts to indentify the fundamental concepts of language, argues that the study of language reveals hidden facts about the mind, and looks at the impact of propaganda.

This paper defends an orthodox model of the linguistic intuitions which form a central source of evidence for generative grammars. According to this orthodox conception, linguistic intuitions are the upshot of a system of grammatical competence as it interacts with performance systems for perceiving and articulating language. So conceived, probing speakers’ linguistic intuitions allows us to investigate the competence–performance distinction empirically, so as to determine the grammars that speakers are competent in. This model has been attacked by Michael Devitt in (...) his recent book and a series of papers. In its place, Devitt advances a model of linguistic intuitions whereby they are speakers’ theory-laden judgements about the properties of languages. In this paper, I try to make clear the rationale behind the orthodox model and the inadequacies of Devitt's model. (shrink)

Chomsky proposes a reformulation of the theory of transformational generative grammar that takes recent developments in the descriptive analysis of particular ...

Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...

Against the traditional view, Alvin Goldman argues that logic, probability theory, and linguistic analysis cannot by themselves delineate principles of rationality or justified belief. The mind's operations must be taken into account.

In recent years evolutionary psychologists have developed and defended the Massive Modularity Hypothesis, which maintains that our cognitive architecture—including the part that subserves ‘central processing’ —is largely or perhaps even entirely composed of innate, domain-specific computational mechanisms or ‘modules’. In this paper I argue for two claims. First, I show that the two main arguments that evolutionary psychologists have offered for this general architectural thesis fail to provide us with any reason to prefer it to a competing picture of the (...) mind which I call the Library Model of Cognition. Second, I argue that this alternative model is compatible with the central theoretical and methodological commitments of evolutionary psychology. Thus I argue that, at present, the endorsement of the Massive Modularity Hypothesis by evolutionary psychologists is both unwarranted and unmotivated. (shrink)

This article reviews the transition between post-Fregean anti-naturalistic epistemology and contemporary naturalistic epistemologies. It traces the revival of naturalism to Quine’s critique of the "a priori", and Kuhn’s defense of historicism, and use the arguments of Quine and Kuhn to identify a position, "traditional naturalism", that combines naturalistic themes with the claim that epistemology is a normative enterprise. Pleas for more radical versions of naturalism are articulated, and briefly confronted.

The Chomskian revolution in linguistics gave rise to a new orthodoxy about mind and language. Michael Devitt throws down a provocative challenge to that orthodoxy. What is linguistics about? What role should linguistic intuitions play in constructing grammars? What is innate about language? Is there a 'language faculty'? These questions are crucial to our developing understanding of ourselves; Michael Devitt offers refreshingly original answers. He argues that linguistics is about linguistic reality and is not part of psychology; that linguistic rules (...) are not represented in the mind; that speakers are largely ignorant of their language; that speakers' intuitions do not reflect information supplied by the language faculty and are not the main evidence for grammars; that the rules of 'Universal Grammar' are largely, if not entirely, innate structure rules of thought; indeed, that there is little or nothing to the language faculty. Devitt's controversial theses will prove highly stimulating to anyone working on language and the mind. (shrink)

The object of this paper is to show why recent research in the psychology of deductive and probabilistic reasoning does not have.

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)

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality (...) of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of? (shrink)

This chapter addresses the flexibility problem for massive modularity. It argues that massively modular architectures exhibit flexibility largely as a result of context-sensitive competition between modules for the allocation of cognitive resources. Thus, it is the cognitive system as a whole that exhibits flexibility, rather than any particular subsystem within it.

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

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)

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)

We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments. In particular, we consider (i) repeated measurements of a single test consequence of the hypothesis, (ii) measurements of multiple test consequences of the hypothesis, (iii) theoretical support for the reliability of the instrument, and (iv) calibration procedures. We evaluate these strategies on their relative merits under idealized conditions and show some surprising (...) repercussions on the variety-of-evidence thesis and the Duhem-Quine thesis. (shrink)

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

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)

The claim that the human cognitive system tends to allocate resources to the processing of available inputs according to their expected relevance is at the basis of relevance theory. The main thesis of this chapter is that this allocation can be achieved without computing expected relevance. When an input meets the input condition of a given modular procedure, it gives this procedure some initial level of activation. Input-activated procedures are in competition for the energy resources that would allow them to (...) follow their full course. What determines which of the procedures in competition get sufficient resources to trigger their full operation is the dynamics of their activation. This dynamics depend both on the prior degree of mobilisation of a modular procedure and on the activation that propagates from other active modules. It is quite conceivable also that the mobilisation of some procedures has inhibitory effects on some others. The relevance-theoretic claim is that, at every instant, this dynamics of activation provides rough physiological indicators of expected relevance. The flow of energy in the system is locally regulated by these indicators. As a result, those input-procedure combinations that have the greatest expected relevance are the more likely ones to receive sufficient energy to follow their course. (shrink)