In this companion volume to Warrant: The Current Debate, Plantinga develops an original approach to the question of epistemic warrant; that is what turns true belief into knowledge. He argues that what is crucial to warrant is the proper functioning of one's cognitive faculties in the right kind of cognitive environment.

This chapter investigates the extent to which claims of massive modular organization of the mind (espoused by some members of the evolutionary psychology research program) are consistent with the main elements of the simple heuristics research program. A number of potential sources of conflict between the two programs are investigated and defused. However, the simple heuristics program turns out to undermine one of the main arguments offered in support of massive modularity, at least as the latter is generally understood by (...) philosophers. So one result of the argument will be to force us to re-examine the way in which the notion of modularity in cognitive science should best be characterized, if the thesis of massive modularity isn’t to be abandoned altogether. What is at stake in this discussion, is whether there is a well-motivated notion of ‘module’ such that we have good reason to think that the human mind must be massively modular in its organization. I shall be arguing (in the end) that there is. (shrink)

Among the most pervasive and fundamental assumptions in cognitive science is that the human mind (or mind-brain) is a mechanism of some sort: a physical device com- posed of functionally specifiable subsystems. On this view, functional decomposition – the analysis of the overall system into functionally specifiable parts – becomes a central project for a science of the mind, and the resulting theories of cognitive archi- tecture essential to our understanding of human psychology.

INTRODUCTION: TWO KINDS OF RLDUCTIONISM The man who laughs is the one who has not yet heard the terrible news. BERTHOLD BRECHT I propose, in this book, ...

Chiappe and Kukla argue that relevance theory fails to solve the frame problem as defined by Fodor. They are right. They are wrong, however, to take Fodor’s frame problem too seriously. Fodor’s concerns, on the other hand, even though they are wrongly framed, are worth addressing. We argue that Relevance thoery helps address them.

The purpose of this paper is to raise some questions about the idea, which was first made prominent by Gilbert Ryle, and has remained associated with him ever since, that there are at least two types of knowledge (or to put it in a slightly different way, two types of states ascribed by knowledge ascriptions) identified, on the one hand, as the knowledge (or state) which is expressed in the ‘knowing that’ construction (sometimes called, for fairly obvious reasons, ‘propositional’ or (...) ‘factual’ knowledge) and, on the other, as the knowledge (or state) which is ascribed in the ‘knowing how’ construction (sometimes called ‘practical’ knowledge). This idea, which might be said to be Ryle's most lasting philosophical legacy, has, in some vague form, remained part of conventional wisdom in philosophy since he put it forward. My purpose here is fairly accurately described as ‘raising questions’, since both the criticisms of the received view (as I interpret it), and the positive alternative suggestions to be advanced, are, to some extent, tentative and exploratory. The aim is to assemble a broad range of evidence for the conclusion that we need to replace the standard account, to query especially what Ryle suggested as evidence for it, and to explore what seems to me to be the indicated replacement for it. (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 volume puts forward a distinct new theory of direct reference, blending insights from both the Fregean and the Russellian traditions, and fitting the general theory of language understanding used by those working on the pragmatics of natural language.

The frame problem is widely reputed among philosophers to be one of the deepest and most difficult problems of cognitive science. This paper discusses three recent attempts to display this problem: Dennett's problem of ignoring obviously irrelevant knowledge, Haugeland's problem of efficiently keeping track of salient side effects, and Fodor's problem of avoiding the use of kooky concepts. In a negative vein, it is argued that these problems bear nothing but a superficial similarity to the frame problem of AI, so (...) that they do not provide reasons to disparage standard attempts to solve it. More positively, it is argued that these problems are easily solved by slight variations on familiar AI themes. Finally, some discussion is devoted to more difficult problems confronting AI. (shrink)

The point of this paper is to provide a principled framework for a naturalistic, interactivist-constructivist model of rational capacity and a sketch of the model itself, indicating its merits. Being naturalistic, it takes its orientation from scientific understanding. In particular, it adopts the developing interactivist-constructivist understanding of the functional capacities of biological organisms as a useful naturalistic platform for constructing such higher order capacities as reason and cognition. Further, both the framework and model are marked by the finitude and fallibility (...) that science attributes to organisms, with their radical consequences, and also by the individual and collective capacities to improve their performances that learning organisms display. Part A prepares the ground for the exposition through a critique of the dominant Western analytic tradition in rationalising science, followed by a brief exposition of the naturalist framework that will be employed to frame the construction. This results in two sets of guidelines for constructing an alternative. Part B provides the new conception of reason as a rich complex of processes of improvement against epistemic values, and argues its merits. It closes with an account of normativity and our similarly developing rational knowledge of it, including (reflexively) of reason itself. (shrink)

In his bookMinimal Rationality (1986), Christopher Cherniak draws deep and widespread conclusions from our finitude, and not only for philosophy but also for a wide range of science as well. Cherniak's basic idea is that traditional philosophical theories of rationality represent idealisations that are inaccessible to finite rational agents. It is the purpose of this paper to apply a theory of idealisation in science to Cherniak's arguments. The heart of the theory is a distinction between idealisations that represent reversible, solely (...) quantitative simplifications and those that represent irreversible, degenerate idealisations which collapse out essential theoretical structure. I argue that Cherniak's position is best understood as assigning the latter status to traditional rationality theories and that, so understood, his arguments may be illuminated, expanded, and certain common criticisms of them rebutted. The result, however, is a departure from traditional, formalist theories of rationality of a more radical kind than Cherniak contemplates, with widespread ramifications for philosophical theory, especially philosophy of science itself. (shrink)

The idea that human thinking and machine computing are "radically the same" provides the central theme for this marvelously lucid and witty book on...

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)

How we see and how we visualize: why the scientific account differs from our experience.

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)

(From the Press's Website) -/- Winner of the 2004 Lakatos Prize, Thought in a Hostile World is an exploration of the evolution of cognition, especially human cognition, by one of today's foremost philosophers of biology and of mind. Features an exploration of the evolution of human cognition. Written by one of today’s foremost philosophers of mind and language. Presents a set of analytic tools for thinking about cognition and its evolution. Offers a critique of nativist, modular versions of evolutionary psychology, (...) rejecting the example of language as a model for thinking about human cognitive capacities. Applies to the areas of cognitive science, philosophy of mind, and evolutionary psychology. -/- . (shrink)

This is a new release of the original 1949 edition.

This book defends a novel theory of singular concepts, emphasizing the pragmatic requirements of singular concept possession and arguing that these requirements must be understood to institute traditions and policies of thought.

Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about (...) fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions. (shrink)

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

This book is a comprehensive development and defense of one of the guiding assumptions of evolutionary psychology: that the human mind is composed of a large number of semi-independent modules. The Architecture of the Mind has three main goals. One is to argue for massive mental modularity. Another is to answer a 'How possibly?' challenge to any such approach. The first part of the book lays out the positive case supporting massive modularity. It also outlines how the thesis should best (...) be developed, and articulates the notion of 'module' that is in question. Then the second part of the book takes up the challenge of explaining how the sorts of flexibility and creativity that are distinctive of the human mind could possibly be grounded in the operations of a massive number of modules.Peter Carruthers's third aim is to show how the various components of the mind are likely to be linked and interact with one another - indeed, this is crucial to demonstrating how the human mind, together with its familiar capacities, can be underpinned by a massively modular set of mechanisms. He outlines and defends the basic framework of a perception / belief / desire / planning / motor-control architecture, as well as detailing the likely components and their modes of connectivity. Many specific claims about the place within this architecture of natural language, of a mind-reading system, and others are explained and motivated. A number of novel proposals are made in the course of these discussions, one of which is that creative human thought depends upon a prior kind of creativity of action.Written with unusual clarity and directness, and surveying an extensive range of research in cognitive science, this book will be essential reading for anyone with an interest in the nature and organization of the mind. (shrink)

Many philosophers believe that there is a fundamental distinction between knowing that something is the case and knowing how to do something. According to Gilbert Ryle, to whom the insight is credited, knowledge-how is an ability, which is in turn a complex of dispositions. Knowledge-that, on the other hand, is not an ability, or anything similar. Rather, knowledge-that is a relation between a thinker and a true proposition.

Much research in AI (and cognitive science, more broadly) proceeds on the assumption that there is a difference between being well-informed and being smart. Being well-informed has to do, roughly, with the content of one’s representations--with their truth and the range of subjects they cover. Being smart, on the other hand, has to do with one’s ability to process these representations and with packaging them in a form that allows them to be processed efficiently. The main theoretical concern of artificial (...) intelligence research is to solve "process-and-form" problems: problems with finding processes and representational formats that enable us to understand how a computer could be smart. (shrink)

For many of the authors in this volume, this is the second attempt to explore what McCarthy and Hayes (1969) first called the “Frame Problem”. Since the first compendium (Pylyshyn, 1987), nicely summarized here by Ronald Loui, there have been several conferences and books on the topic. Their goals range from providing a clarification of the problem by breaking it down into subproblems (and sometimes declaring the hard subproblems to not be the_ real_ Frame Problem), to providing formal “solutions” to (...) certain aspects of the problem. But more often the message has been that the problem is not solvable except in a piecemeal way in special circumstances by some sort of heuristic approximations. It has sometimes also been said that solving the Frame Problem is not only an unachievable goal, but it is also an unnecessary one since_ humans_ do not solve it either; we simply get along as best we can and deal with the problem of planning in ways that, to use Dennett’s phrase, is “good enough for government work”. (shrink)