How can we think about things in the outside world? There is still no widely accepted theory of how mental representations get their meaning. In light of pioneering research, Nicholas Shea develops a naturalistic account of the nature of mental representation with a firm focus on the subpersonal representations that pervade the cognitive sciences.

Fodor’s radical concept nativism flowed from his view that hypothesis testing is the only route to concept acquisition. Many have successfully objected to the overly-narrow restriction to learning by hypothesis testing. Existing representations can be connected to a new representational vehicle so as to constitute a sustaining mechanism for a new representation, without the new representation thereby being constituted by or structured out of the old. This paper argues that there is also a deeper objection. Connectionism shows that a more (...) fundamental assumption underpinning the debate can also be rejected: the assumption that the development of a new representation must be explained in content-involving terms if innateness is to be avoided. -/- Fodor has argued that connectionism offers no new resources to explain concept acquisition: unless it is merely an uninteresting claim about neural implementation, connectionism’s defining commitment to distributed representations reduces to the claim that some representations are structured out of others (which is the old, problematic research programme). Examination of examples of representational development in connectionist networks shows, however, that some such models explain the development of new representational capacities in non-representational terms. They illustrate the possibility of representational development that is not explicable-by-content. Connectionist representations can be distributed in an important sense, which is incompatible with the assumption of explanation-by-content: they can be distributed over non-representational resources that account for their development. Rejecting the assumption of explanation-by-content thereby opens up a more radical way of rejecting Fodor’s argument for radical concept nativism. (shrink)

When a piece of fruit is in a bowl, and the bowl is on a table, we appreciate not only the individual objects and their features, but also the relations containment and support, which abstract away from the particular objects involved. Independent representation of roles (e.g., containers vs. supporters) and “fillers” of those roles (e.g., bowls vs. cups, tables vs. chairs) is a core principle of language and higherlevel reasoning. But does such role-filler independence also arise in automatic visual processing? (...) Here, we show that it does, by exploring a surprising error that such independence can produce. In four experiments, participants saw a stream of images containing different objects arranged in forcedynamic relations — e.g., a phone contained in a basket, a marker resting on a garbage can, or a knife sitting in a cup. Participants had to respond to a single target image (e.g., a phone in a basket) within a stream of distractors presented under time constraints. Surprisingly, even though participants completed this task quickly and accurately, they false-alarmed more often to images matching the target’s relational category than to those that did not — even when those images involved completely different objects. In other words, participants searching for a phone in a basket were more likely to mistakenly respond to a knife in a cup than to a marker on a garbage can. Follow-up experiments ruled out strategic responses and also controlled for various confounding image features. We suggest that visual processing represents relations abstractly, in ways that separate roles from fillers. (shrink)

This is the most comprehensive book ever published on philosophical methodology. A team of thirty-eight of the world's leading philosophers present original essays on various aspects of how philosophy should be and is done. The first part is devoted to broad traditions and approaches to philosophical methodology. The entries in the second part address topics in philosophical methodology, such as intuitions, conceptual analysis, and transcendental arguments. The third part of the book is devoted to essays about the interconnections between philosophy (...) and neighbouring fields, including those of mathematics, psychology, literature and film, and neuroscience. (shrink)

This chapter describes the conceptual foundations of cognitive science during its establishment as a science in the 20th century. It is organized around the core ideas of individual agency as its basic explanans and information-processing as its basic explanandum. The latter consists of a package of ideas that provide a mathematico-engineering framework for the philosophical theory of materialism.

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence (...) from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

Tracing the leading role of emotions in the evolution of the mind, a philosopher and a psychologist pair up to reveal how thought and culture owe less to our faculty for reason than to our capacity to feel. Many accounts of the human mind concentrate on the brain’s computational power. Yet, in evolutionary terms, rational cognition emerged only the day before yesterday. For nearly 200 million years before humans developed a capacity to reason, the emotional centers of the brain were (...) hard at work. If we want to properly understand the evolution of the mind, we must explore this more primal capability that we share with other animals: the power to feel. Emotions saturate every thought and perception with the weight of feelings. The Emotional Mind reveals that many of the distinctive behaviors and social structures of our species are best discerned through the lens of emotions. Even the roots of so much that makes us uniquely human—art, mythology, religion—can be traced to feelings of caring, longing, fear, loneliness, awe, rage, lust, playfulness, and more. From prehistoric cave art to the songs of Hank Williams, Stephen T. Asma and Rami Gabriel explore how the evolution of the emotional mind stimulated our species’ cultural expression in all its rich variety. Bringing together insights and data from philosophy, biology, anthropology, neuroscience, and psychology, The Emotional Mind offers a new paradigm for understanding what it is that makes us so unique. (shrink)

An early, very preliminary edition of this book was circulated in 1962 under the title Set-theoretical Structures in Science. There are many reasons for maintaining that such structures play a role in the philosophy of science. Perhaps the best is that they provide the right setting for investigating problems of representation and invariance in any systematic part of science, past or present. Examples are easy to cite. Sophisticated analysis of the nature of representation in perception is to be found already (...) in Plato and Aristotle. One of the great intellectual triumphs of the nineteenth century was the mechanical explanation of such familiar concepts as temperature and pressure by their representation in terms of the motion of particles. A more disturbing change of viewpoint was the realization at the beginning of the twentieth century that the separate invariant properties of space and time must be replaced by the space-time invariants of Einstein's special relativity. Another example, the focus of the longest chapter in this book, is controversy extending over several centuries on the proper representation of probability. The six major positions on this question are critically examined. Topics covered in other chapters include an unusually detailed treatment of theoretical and experimental work on visual space, the two senses of invariance represented by weak and strong reversibility of causal processes, and the representation of hidden variables in quantum mechanics. The final chapter concentrates on different kinds of representations of language, concluding with some empirical results on brain-wave representations of words and sentences. (shrink)

[This is an earlier (1997), much longer and more detailed version of my entry on LOTH in the _Stanford Encyclopedia of Philosophy_] The Language of Thought Hypothesis (LOTH) is an empirical thesis about thought and thinking. For their explication, it postulates a physically realized system of representations that have a combinatorial syntax (and semantics) such that operations on representations are causally sensitive only to the syntactic properties of representations. According to LOTH, thought is, roughly, the tokening of a representation that (...) has a syntactic (constituent) structure with an appropriate semantics. Thinking thus consists in syntactic operations defined over representations. Most of the arguments for LOTH derive their strength from their ability to explain certain empirical phenomena like productivity, systematicity of thought and thinking. (shrink)

In quantum computing, where algorithms exist that can solve computational problems more efficiently than any known classical algorithms, the elimination of errors that result from external disturbances or from imperfect gates has become the ...

In this book, Mark Rowlands challenges the Cartesian view of the mind as a self-contained monadic entity, and offers in its place a radical externalist or environmentalist model of cognitive processes. Cognition is not something done exclusively in the head, but fundamentally something done in the world. Drawing on both evolutionary theory and a detailed examination of the processes involved in perception, memory, thought and language use, Rowlands argues that cognition is, in part, a process whereby creatures manipulate and exploit (...) relevant objects in their environment. It is not simply an internal process of information processing; equally significantly, it is an external process of information processing. This innovative book provides a foundation for an unorthodox but increasingly popular view of the nature of cognition. (shrink)

On a modified view of embodied cognition, I argue that the conceptual structure of some present-day’s abstract artifact concepts such as PIECE OF MUSIC or PIECE OF ART can be effectively explained if it is taken into account that “visual recordings” of first observed result objects played a major role in developing abstract artifact concepts.

The topic of this dissertation is the nature of linguistic competence, the capacity to understand and produce sentences of natural language. I defend the empiricist account of linguistic competence embedded in the connectionist cognitive science. This strand of cognitive science has been opposed to the traditional symbolic cognitive science, coupled with transformational-generative grammar, which was committed to nativism due to the view that human cognition, including language capacity, should be construed in terms of symbolic representations and hardwired rules. Similarly, linguistic (...) competence in this framework was regarded as being innate, rule-governed, domain-specific, and fundamentally different from performance, i.e., idiosyncrasies and factors governing linguistic behavior. I analyze state-of-the-art connectionist, deep learning models of natural language processing, most notably large language models, to see what they can tell us about linguistic competence. Deep learning is a statistical technique for the classification of patterns through which artificial intelligence researchers train artificial neural networks containing multiple layers that crunch a gargantuan amount of textual and/or visual data. I argue that these models suggest that linguistic competence should be construed as stochastic, pattern-based, and stemming from domain-general mechanisms. Moreover, I distinguish syntactic from semantic competence, and I show for each the ramifications of the endorsement of a connectionist research program as opposed to the traditional symbolic cognitive science and transformational-generative grammar. I provide a unifying front, consisting of usage-based theories, a construction grammar approach, and an embodied approach to cognition to show that the more multimodal and diverse models are in terms of architectural features and training data, the stronger the case is for the connectionist linguistic competence. I also propose to discard the competence vs. performance distinction as theoretically inferior so that a novel and integrative account of linguistic competence originating in connectionism and empiricism that I propose and defend in the dissertation could be put forward in scientific and philosophical literature. (shrink)

[Edited from Conclusion section:] We have looked at various challenging issues to do with getting connectionism to cope with high-level cognitive activities such a reasoning and natural language understanding. The issues are to do with various facets of generalization that are not commonly noted. We have been concerned in particular with the special forms these issues take in the arena of propositional attitude processing. The main problems we have looked at are: (1) The need to construct explicit representations of generalizations, (...) not just generalize correctly to individual cases; (2) The need to be able to match two or more complex short-term information structures, to enable rapid generalization from recent examples rather than from long-term memories; (3) The need to represent and reason with anomalous combinations of concepts; (4) The need to perform embedded reasoning. This presents special problems for systems using non-concatenative representations (as in mainstream connectionist approaches). We also touched on vague quantification in attitude report complements. Neither this topic nor that of analogies between short-term structures (point 2) has been adequately addressed in the symbolic framework, let alone in connectionism. -/- The opportunities and problems covered are put forward as things worth being optimistic about or pessimistic about, respectively. They are not put forward as decisive arguments for or against connectionism. The hope is that this chapter contributes to a greater understanding of the connectionist/symbolist gap by presenting some unusual issues and by throwing new light on some well known ones. (shrink)

Mental imagery (varieties of which are sometimes colloquially refered to as “visualizing,” “seeing in the mind's eye,” “hearing in the head,” “imagining the feel of,” etc.) is quasi-perceptual experience; it resembles perceptual experience, but occurs in the absence of the appropriate external stimuli. It is also generally understood to bear intentionality (i.e., mental images are always images of something or other), and thereby to function as a form of mental representation. Traditionally, visual mental imagery, the most discussed variety, was thought (...) to be caused by the presence of picturelike representations (mental images) in the mind, soul, or brain, but this is no longer universally accepted. (shrink)

A lengthy debate in the philosophy of the cognitive sciences has turned on whether the phenomenon known as ‘systematicity’ of language and thought shows that connectionist explanatory aspirations are misguided. We investigate the issue of just which phenomenon ‘systematicity’ is supposed to be. The much-rehearsed examples always suggest that being systematic has something to do with ways in which some parts of expressions in natural languages (and, more conjecturally, some parts of thoughts) can be substituted for others without altering well-formedness. (...) We show that under one construal this yields a grossly weak claim that is not just compatible with a narrow version of associationist psychology but essentially coincides with a formalization of its descriptive power. Under another construal we get a claim (apparently unintended) that requires natural languages to fall within the context-free class, a claim that most linguists regard as too strong. Looking more closely at this proposed reconstruction of systematicity leads us to endorse, with further illustrations, the suggestion of Johnson (2004) that systematicity as a matter of substitutability of co-categorial constituents for one another does not appearto hold of natural languages at all. The appeal of the ill-delineated notion of systematicity may lie in the fact that within certain subclasses of lexical items mutual intersubstitutability does seem to hold, and theexplanation for that lies in a limitation on human memory: we simply cannot learn separate privileges of syntactic distribution for all of the huge number of words and phrases that we know. (shrink)

Eliminative materialism (or eliminativism) is the radical claim that our ordinary, common-sense understanding of the mind is deeply wrong and that some or all of the mental states posited by common-sense do not actually exist. Descartes famously challenged much of what we take for granted, but he insisted that, for the most part, we can be confident about the content of our own minds. Eliminative materialists go further than Descartes on this point, since they challenge of the existence of various (...) mental states that Descartes took for granted. (shrink)

The notion of a "mental representation" is, arguably, in the first instance a theoretical construct of cognitive science. As such, it is a basic concept of the Computational Theory of Mind, according to which cognitive states and processes are constituted by the occurrence, transformation and storage (in the mind/brain) of information-bearing structures (representations) of one kind or another.

Over the past thirty years, it is been common to hear the mind likened to a digital computer. This essay is concerned with a particular philosophical view that holds that the mind literally is a digital computer (in a specific sense of “computer” to be developed), and that thought literally is a kind of computation. This view—which will be called the “Computational Theory of Mind” (CTM)—is thus to be distinguished from other and broader attempts to connect the mind with computation, (...) including (a) various enterprises at modeling features of the mind using computational modeling techniques, and (b) employing some feature or features of production-model computers (such as the stored program concept, or the distinction between hardware and software) merely as a guiding metaphor for understanding some feature of the mind. This entry is therefore concerned solely with the Computational Theory of Mind (CTM) proposed by Hilary Putnam [1961] and developed most notably for philosophers by Jerry Fodor [1975, 1980, 1987, 1993]. The senses of ‘computer’ and ‘computation’ employed here are technical; the main tasks of this entry will therefore be to elucidate: (a) the technical sense of ‘computation’ that is at issue, (b) the ways in which it is claimed to be applicable to the mind, (c) the philosophical problems this understanding of the mind is claimed to solve, and (d) the major criticisms that have accrued to this view. (shrink)

Combining physics, mathematics and computer science, quantum computing and its sister discipline of quantum information have developed in the past few decades from visionary ideas to two of the most fascinating areas of quantum theory. General interest and excitement in quantum computing was initially triggered by Peter Shor (1994) who showed how a quantum algorithm could exponentially “speed-up” classical computation and factor large numbers into primes far more efficiently than any (known) classical algorithm. Shor’s algorithm was soon followed by several (...) other algorithms that aimed to solve combinatorial and algebraic problems, and in the years since theoretical study of quantum systems serving as computational devices has achieved tremendous progress. Common belief has it that the implementation of Shor’s algorithm on a large scale quantum computer would have devastating consequences for current cryptography protocols which rely on the premise that all known classical worst-case algorithms for factoring take time exponential in the length of their input (see, e.g., Preskill 2005). Consequently, experimentalists around the world are engaged in attempts to tackle the technological difficulties that prevent the realisation of a large scale quantum computer. But regardless whether these technological problems can be overcome (Unruh 1995; Ekert and Jozsa 1996; Haroche and Raimond 1996), it is noteworthy that no proof exists yet for the general superiority of quantum computers over their classical counterparts. -/- The philosophical interest in quantum computing is manifold. From a social-historical perspective, quantum computing is a domain where experimentalists find themselves ahead of their fellow theorists. Indeed, quantum mysteries such as entanglement and nonlocality were historically considered a philosophical quibble, until physicists discovered that these mysteries might be harnessed to devise new efficient algorithms. But while the technology for harnessing the power of 50–100 qubits (the basic unit of information in the quantum computer) is now within reach (Preskill 2018), only a handful of quantum algorithms exist, and the question of whether these can truly outperform any conceivable classical alternative is still open. From a more philosophical perspective, advances in quantum computing may yield foundational benefits. For example, it may turn out that the technological capabilities that allow us to isolate quantum systems by shielding them from the effects of decoherence for a period of time long enough to manipulate them will also allow us to make progress in some fundamental problems in the foundations of quantum theory itself. Indeed, the development and the implementation of efficient quantum algorithms may help us understand better the border between classical and quantum physics (Cuffaro 2017, 2018a; cf. Pitowsky 1994, 100), and perhaps even illuminate fundamental concepts such as measurement and causality. Finally, the idea that abstract mathematical concepts such as computability and complexity may not only be translated into physics, but also re-written by physics bears directly on the autonomous character of computer science and the status of its theoretical entities—the so-called “computational kinds”. As such it is also relevant to the long-standing philosophical debate on the relationship between mathematics and the physical world. (shrink)

In this paper we consider the importance of using a humanoid physical form for a certain proposed kind of robotics, that of theory grounding. Theory grounding involves grounding the theory skills and knowledge of an embodied artificially intelligent system by developing theory skills and knowledge from the bottom up. Theory grounding can potentially occur in a variety of domains, and the particular domain considered here is that of language. Language is taken to be another “problem space” in which a system (...) can explore and discover solutions. We argue that because theory grounding necessitates robots experiencing domain information, certain behavioral-form aspects, such as abilities to socially smile, point, follow gaze, and generate manual gestures, are necessary for robots grounding a humanoid theory of language. (shrink)

Jerry Fodor argues that Darwin was wrong about "natural selection" because (1) it is only a tautology rather than a scientific law that can support counterfactuals ("If X had happened, Y would have happened") and because (2) only minds can select. Hence Darwin's analogy with "artificial selection" by animal breeders was misleading and evolutionary explanation is nothing but post-hoc historical narrative. I argue that Darwin was right on all counts. Until Darwin's "tautology," it had been believed that either (a) God (...) had created all organisms as they are, or (b) organisms had always been as they are. Darwin revealed instead that (c) organisms have heritable traits that evolved across time through random variation, with survival and reproduction in (changing) environments determining (mindlessly) which variants were successfully transmitted to the next generation. This not only provided the (true) alternative (c), but also the methodology for investigating which traits had been adaptive, how and why; it also led to the discovery of the genetic mechanism of the encoding, variation and evolution of heritable traits. Fodor also draws erroneous conclusions from the analogy between Darwinian evolution and Skinnerian reinforcement learning. Fodor’s skepticism about both evolution and learning may be motivated by an overgeneralization of Chomsky’s “poverty of the stimulus argument” -- from the origin of Universal Grammar (UG) to the origin of the “concepts” underlying word meaning, which, Fodor thinks, must be “endogenous,” rather than evolved or learned. (shrink)

Cognitive pragmatics is concerned with the mental processes involved in intentional communication. I discuss a few issues that may help clarify the relationship between this area and the broader cognitive science and the contribution that they give, or might give, to each other. Rather than dwelling on the many technicalities of the various theories of communication that have been advanced, I focus on the different conceptions of the nature and the architecture of the mind/brain that underlie them. My aims are, (...) first, to introduce and defend mentalist views of communication in general; second, to defend one such view, namely that communication is a cognitive competence, that is, a faculty, and the underlying idea that the architecture of the mind/brain is domain-specific; and, third, to review the (scarce) neuropsychological evidence that bears on these issues. (shrink)

Are minds really dynamical or are they really symbolic? Because minds are bundles of computations, and because computation is always a matter of interpretation of one system by another, minds are necessarily symbolic. Because minds, along with everything else in the universe, are physical, and insofar as the laws of physics are dynamical, minds are necessarily dynamical systems. Thus, the short answer to the opening question is “yes.” It makes sense to ask further whether some of the computations that constitute (...) a human mind are constrained by functional, algorithmic, or implementational factors to be essentially of the discrete symbolic variety (even if they supervene on an apparently continuous dynamical substrate). I suggest that here too the answer is “yes” and discuss the need for such discrete, symbolic cognitive computations in communication-related tasks. (shrink)

Heuristics are often invoked in the philosophical, psychological, and cognitive science literatures to describe or explain methodological techniques or "shortcut" mental operations that help in inference, decision-making, and problem-solving. Yet there has been surprisingly little philosophical work done on the nature of heuristics and heuristic reasoning, and a close inspection of the way(s) in which "heuristic" is used throughout the literature reveals a vagueness and uncertainty with respect to what heuristics are and their role in cognition. This dissertation seeks to (...) remedy this situation by motivating philosophical inquiry into heuristics and heuristic reasoning, and then advancing a theory of how heuristics operate in cognition. I develop a positive working characterization of heuristics that is coherent and robust enough to account for a broad range of phenomena in reasoning and inference, and makes sense of empirical data in a systematic way. I then illustrate the work this characterization does by considering the sorts of problems that many philosophers believe heuristics solve, namely those resulting from the so-called frame problem. Considering the frame problem motivates the need to gain a better understanding of how heuristics work and the cognitive structures over which they operate. I develop a general theory of cognition which I argue underwrites the heuristic operations that concern this dissertation. I argue that heuristics operate over highly organized systems of knowledge, and I offer a cognitive architecture to accommodate this view. I then provide an account of the systems of knowledge that heuristics are supposed to operate over, in which I suggest that such systems of knowledge are concepts. The upshot, then, is that heuristics operate over concepts. I argue, however, that heuristics do not operate over conceptual content, but over metainformational relations between activated and primed concepts and their contents. Finally, to show that my thesis is empirically adequate, I consider empirical evidence on heuristic reasoning and argue that my account of heuristics explains the data. (shrink)

In this section, we will start with an influential attempt to define `intelligence', and then we will move to a consideration of how human intelligence is to be investigated on the machine model. The last part of the section will discuss the relation between the mental and the biological.

This thesis investigates the nature of the relation between mental representations in successful verbal communication, thought attribution, agreement, and disagreement — a relation which I call “samethinking”. The nature of samethinking raises several foundational questions about the nature of (non-natural) meaning, and the cognitive underpinnings of the emergence of culture. It bears on long-lasting puzzles in the philosophy of mind and language (such as Frege’s puzzle and Kripke’s puzzle about belief). Samethinking does not amount to sharing a reference (with “sharing" (...) I refer to two or more thinkers having something in common): it is more demanding. How can we explain and characterize this relation, more stringent than coreference, that is instantiated by a pair of thoughts when samethinking takes place? It is often assumed that this relation involves sharing a thought content more fine-grained than reference. In this thesis, I argue that the issue is more complex than what has been commonly assumed, and I suggest an alternative model in which sharing thought content is not necessary. (shrink)

The Tunguska Mystery by Vladimir Rubtsov Steven J. Dick Witness to Roswell: Unmasking the Government’s Biggest Cover-Up by Thomas J. Carey & Donald R. Schmitt Bruce Maccabee The Roswell Legacy: The Untold Story of the First Military Officer at the 1947 Crash Site by Jesse Marcel, Jr., & Linda Marcel Barry Greenwood Art, Life, and UFOs: A Memoir by Budd Hopkins Stuart Appelle Bigfoot: The Life and Times of a Legend by Joshua B. Buhs; and Anatomy of a Beast: Obsession (...) and Myth on the Trail of Bigfoot by Michael McLeod John Bindernagel Philosophy in the Flesh: The Embodied Mind and Its Challenges to Western Thought by George Lakoff and Mark Johnson Stephen R. Palmquist Neither Brain nor Ghost: A Non-Dualist Alternative to the Mind–Brain Identity Theory by W. Teed Rockwell; Radical Embodied Cognitive Science by Anthony Chemero Stan V. McDaniel Synchronocity: Multiple Perspectives on Meaningful Coincidence edited by Lance Storm Frank Pasciuti Laboratories of Faith: Mesmerism, Spiritism, and Occultism in Modern France by John Warne Monroe Renaud Evrard The Spiritual Anatomy of Emotion: How Feelings Link the Brain, the Body, and the Sixth Sense by Michael A. Jawer with Marc S. Micozzi Bryan J. Williams La Connaissance Supranormale, étude Expérimentale by Eugène Osty. Supernormal Faculties in Man: An Experimental Study by Eugene Osty Thomas Rabeyron Phénomènes Psychiques au Moment de la Mort by Ernest Bozzano; Deathbed Visions: The Psychical Experiences of the Dying by Sir William F. Barrett Carlos S. Alvarado Allan Kardec und der Spiritismus in Lyon um 1900. Geisterkommunikation als Soziales Phänomen by Katrin Heuser Andreas Sommer Further Book of Note: El Mundo Oculto de Los Sueños by Alejandro Parra Carlos Adrián Hernández Tavares and Stanley Krippner. (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)

In this paper, we pursue three general aims: (I) We will define a notion of fundamental opacity and ask whether it can be found in High Energy Physics (HEP), given the involvement of machine learning (ML) and computer simulations (CS) therein. (II) We identify two kinds of non-fundamental, contingent opacity associated with CS and ML in HEP respectively, and ask whether, and if so how, they may be overcome. (III) We address the question of whether any kind of opacity, contingent (...) or fundamental, is unique to ML or CS, or whether they stand in continuity to kinds of opacity associated with other scientific research. (shrink)

Deep appreciation of the relevance of emotion to epistemology requires a rich account of how emotional mental states such as happiness, sadness and desire interact with cognitive states such as belief and doubt. Analytic philosophy since Gottlob Frege and Bertrand Russell has assumed that such mental states are propositional attitudes, which are relations between a self and a proposition, an abstract entity constituting the meaning of a sentence. This chapter shows the explanatory defects of the doctrine of propositional attitudes, and (...) proposes instead that beliefs, desires, and emotions should be construed naturalistically using current understanding of brain mechanisms. Mental states are patterns of neural activity, not relations between dubious entities such as selves and propositions. From this perspective, it becomes easy to see how cognition and emotion are intertwined, and hence how emotions can be integral to epistemology. I begin by reviewing some of the ways in which emotions are relevant to epistemology: as frequent contributors to the growth of knowledge, as sometime impediments to knowledge acquisition, and as components of knowledge about persons and morality. I then argue that propositional attitudes do not exist, because the selves and the propositions that they purportedly relate do not exist. Thus the doctrine of propositional attitudes is as useless for epistemology as it is for explaining human action. I argue for an alternative construal of mental states as patterns of neural activity, and July 23, 2007 describe how it is possible to give a theoretically rich and empirically supported account of the neurophysiological interconnections of cognition and emotion. Finally, I discuss the epistemological significance of this naturalistic, materialist reconstrual of cognitions and emotions. (shrink)

6. Seeing With the Mind’s Eye 1: The Puzzle of Mental Imagery .................................................6-1 6.1 What is the puzzle about mental imagery?..............................................................................6-1 6.2 Content, form and substance of representations ......................................................................6-6 6.3 What is responsible for the pattern of results obtained in imagery studies?.................................6-8..

I was asked to develop a course “Philosophy and Cognitive Science” to be taught for the first time in Spring 1995 in the Philosophy Department at the University of Alberta. Since my cognitive science-related interests are focussed more towards philosophy mixed with artificial intelligence (A I) and linguistics than towards (say) neuroscience or anthropology, I decided to slant the course in t hat direction. The departmental intent was that this should be an upper-level course, but with no spe cific prerequisite (...) courses. This meant that while there was a “three previous courses in philosophy ” prerequisite, the students could not be expected to have taken any particular course, as (say) a phil osophy of mind course or a logic course. Further, I had in mind that the course would be part of an initiative to create an undergraduate program in Cognitive Science at the University of Alberta, and s o I encouraged students from linguistics, computer science, and psychology who had taken courses in their department like “Language and Mind”, “Introduction to AI”, and “Introduction to Cognit ive Science” to take this course even without the philosophy background. This resulted in the class consisting of about a quarter each philosophy, psychology and computer science majors, with the re st being drawn from linguistics, education, and anthropology. And although this distribution of stud ents arguably lessened the philosophical sophistication of both the lectures and the class discussion, I (and the students, I believe) found the perspectives brought to the topic by these other students to be fascinating and quite provocative. (shrink)

Is Language the Ultimate Artefact? (henceforth ILUA) was originally published alongside a paper by Andy Clark called Is Language Special? Some remarks on control, coding, and co-ordination (Clark 2004). One concern (among others) of the latter paper was to resist the argument of the former. In this short afterword, I shall attempt a counterresponse to Clark’s resistance. In so doing I hope to reveal, in a new and perhaps clearer way, what the most important issues really are in this (still (...) unresolved) debate. (shrink)

Concepts of space and time are widely developed in physics. However, there is a considerable lack of biologically plausible theoretical frameworks that can demonstrate how space and time dimensions are implemented in the activity of the most complex life-system – the brain with a mind. Brain activity is organized both temporally and spatially, thus representing space-time in the brain. Critical analysis of recent research on the space-time organization of the brain’s activity pointed to the existence of so-called operational space-time in (...) the brain. This space-time is limited to the execution of brain operations of differing complexity. During each such brain operation a particular short-term spatio-temporal pattern of integrated activity of different brain areas emerges within related operational space-time. At the same time, to have a fully functional human brain one needs to have a subjective mental experience. Current research on the subjective mental experience offers detailed analysis of space-time organization of the mind. According to this research, subjective mental experience (subjective virtual world) has definitive spatial and temporal properties similar to many physical phenomena. Based on systematic review of the propositions and tenets of brain and mind space-time descriptions, our aim in this review essay is to explore the relations between the two. To be precise, we would like to discuss the hypothesis that via the brain operational space-time the mind subjective space-time is connected to otherwise distant physical space-time reality. (shrink)

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In (...) this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism and connectionism on the other. We defend the relevance to cognitive science of both computation, in a generic sense that we fully articulate for the first time, and information processing, in three important senses of the term. Our account advances some foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects. (shrink)

Man’s intellectual capacity remains an enigma, as it is both the subject and the means of analysis. If one is to assume quantum-wave dualism in physics then the state of the world depends on the instruments we use for observation. The “paradoxical” nature of investigating human cognition may thus bear inherent limitations. However, studying cognitive models may be less of a seemingly inconsistent endeavor, if “contradictions” may be classified. In this brief exposition, a variety of aspects related to cognitive models (...) are discussed. The authors maintain that modeling the functional “paradoxical nature” of human cognition remains the greatest challenge. Therefore, consciousness aside, models of conscious systems, or rather conscious models of conscious systems, are the main objects of exploration. While intentional systems may seem a good starting point for such an exploration, they lack two important constructs: volition and reflexion. Both concepts, and especially volition, unlike rationality for example, are less discussed in the discourse of cognitive models. Although not devoted to volition or reflexion, this work proposes an increased research interest in these areas. (shrink)

The paper critically reviews Jerry Fodor's book In Critical Condition: Polemic Essays on Cognitive Science and the Philosophy of Mind. It focuses on Fodor's compositionality arguments and their relevance to the following questions: How should concepts be individuated? What has semantics to do with epistemology? Who is right in the debate over classical and connectionist theories of cognition? How can the semantic properties of a mental state be inherited from the semantic properties of the state's constituents? The paper finally argues (...) that Fodor's opposition to functional role semantics might jeopardize his view that semantic compositionality requires appropriate constituent relations between complex and less complex concepts. (shrink)

The contextual mind is found attested in various usages of the term complement, in the background of Kant. The difficulties of Kant's intuitionism are taken up through Quine, but referential opacity is resolved as semantic presence in lived context. A further critique of rationalist linguistics is developed from Jakobson, showing generic functions in thought supporting abstraction, binding and thereby semantic categories. Thus Bolzano's influential philosophy of mathematics and science gives way to a critical view of the ancient heritage acknowledged by (...) Plato. (shrink)