2. Invariant Sensorimotor Features ("Affordances"). To say this is not to declare oneself a Gibsonian, whatever that means. It is merely to point out that what a sensorimotor system can do is determined by what can be extracted from its motor interactions with its sensory input. If you lack sonar sensors, then your sensorimotor system cannot do what a bat's can do, at least not without the help of instruments. Light stimulation affords color vision for those of us with the (...) right sensory apparatus, but not for those of us who are color-blind. The geometric fact that, when we move, the "shadows" cast on our retina by nearby objects move faster than the shadows of further objects means that, for those of us with normal vision, our visual input affords depth perception. From more complicated facts of projective and solid geometry it follows that a 3-dimensional shape, such as, say, a boomerang, can be recognized as being the same shape Ð and the same size Ð even though the size and shape of its shadow on our retinas changes as we move in relation to it or it moves in relation to us. Its shape is said to be invariant under these sensorimotor transformations, and our visual systems can detect and extract that invariance, and translate it into a visual constancy. So we keep seeing a boomerang of the same shape and size even though the shape and size of its retinal shadows keep changing. (shrink)

This article critically examines the views that psychology first came into existence as a discipline ca. 1879, that philosophy and psychology were estranged in the ensuing decades, that psychology finally became scientific through the influence of logical empiricism, and that it should now disappear in favor of cognitive science and neuroscience. It argues that psychology had a natural philosophical phase (from antiquity) that waxed in the seventeenth and eighteenth centuries, that this psychology transformed into experimental psychology ca. 1900, that philosophers (...) and psychologists collaboratively discussed the subject matter and methods of psychology in the first two decades of the twentieth century, that the neobehaviorists were not substantively influenced by the Vienna Circle, that the study of perception and cognition in psychology did not disappear in the behaviorist period and so did not reemerge as a result of artificial intelligence, linguistics, and the computer analogy, that although some psychologists adopted the language-of-thought approach of traditional cognitive science, many did not, and that psychology will not go away because it contributes independently of cognitive science and neuroscience. (shrink)

In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a mind and (...) anorganism. My approach in the current paper isto explore this and other key themes inneurosemantics through the use of computermodels of neural networks embodied and evolvedin virtual organisms. The models allow for thelaying bare of the causal economies of entireyet simple artificial organisms so that therelations between the neural bases of, forinstance, representation in perception andmemory can be regarded in the context of anentire organism. On the basis of thesesimulations, I argue for an account ofneurosemantics adequate for the solution of theeconomy problem. (shrink)

When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches _vehicle_ and _process_ theories of consciousness, respectively. However, while there may be space (...) for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because of the influence exerted, on the one hand, by a large body of research which purports to show that the explicit representation of information in the brain and conscious experience are _dissociable_, and on the other, by the _classical_ computational theory of mind – the theory that takes human cognition to be a species of symbol manipulation. But two recent developments in cognitive science combine to suggest that a reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer reasonable to assume that the dissociability of conscious experience and explicit representation has been adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in cognitive science as it once was. It now has a lively competitor in the form of _connectionism; _and connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It takes the form of the following simple empirical hypothesis: _phenomenal experience consists in the explicit_ _representation of information in neurally realized PDP networks_.. (shrink)

This paper discusses an "expressive constraint" on accounts of thought and language which requires that when a speaker expresses a belief by sincerely uttering a sentence, the utterance and the belief have the same content. It will be argued that this constraint should be viewed as expressing a conceptual connection between thought and language rather than a mere empirical generalization about the two. However, the most obvious accounts of the relation between thought and language compatible with the constraint (giving an (...) independent account of one of either linguistic meaning or thought content and understanding the other in terms of it) both face serious difficulties. Because of this, the following will suggest an alternative picture of the relation between thought and language that remains compatible with the constraint. (shrink)

1. The Situation in Cognition 2. Situated Cognition: A Potted Recent History 3. Extensions in Biology, Computation, and Cognition 4. Articulating the Idea of Cognitive Extension 5. Are Some Resources Intrinsically Non-Cognitive? 6. Is Cognition Extended or Only Embedded? 7. Letting Nature Take Its Course.

Many people have argued that the evolution of the human language faculty cannot be explained by Darwinian natural selection. Chomsky and Gould have suggested that language may have evolved as the by-product of selection for other abilities or as a consequence of as-yet unknown laws of growth and form. Others have argued that a biological specialization for grammar is incompatible with every tenet of Darwinian theory – that it shows no genetic variation, could not exist in any intermediate forms, confers (...) no selective advantage, and would require more evolutionary time and genomic space than is available. We examine these arguments and show that they depend on inaccurate assumptions about biology or language or both. Evolutionary theory offers clear criteria for when a trait should be attributed to natural selection: complex design for some function, and the absence of alternative processes capable of explaining such complexity. Human language meets these criteria: Grammar is a complex mechanism tailored to the transmission of propositional structures through a serial interface. Autonomous and arbitrary grammatical phenomena have been offered as counterexamples to the position that language is an adaptation, but this reasoning is unsound: Communication protocols depend on arbitrary conventions that are adaptive as long as they are shared. Consequently, language acquisition in the child should systematically differ from language evolution in the species, and attempts to analogize them are misleading. Reviewing other arguments and data, we conclude that there is every reason to believe that a specialization for grammar evolved by a conventional neo-Darwinian process. (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)

Radical concept nativism is the thesis that virtually all lexical concepts are innate. Notoriously endorsed by Jerry Fodor (1975, 1981), radical concept nativism has had few supporters. However, it has proven difficult to say exactly what’s wrong with Fodor’s argument. We show that previous responses are inadequate on a number of grounds. Chief among these is that they typically do not achieve sufficient distance from Fodor’s dialectic, and, as a result, they do not illuminate the central question of how new (...) primitive concepts are acquired. To achieve a fully satisfactory response to Fodor’s argument, one has to juxtapose questions about conceptual content with questions about cognitive development. To this end, we formulate a general schema for thinking about how concepts are acquired and then present a detailed illustration. (shrink)

To compute is to execute an algorithm. More precisely, to say that a device or organ computes is to say that there exists a modelling relationship of a certain kind between it and a formal specification of an algorithm and supporting architecture. The key issue is to delimit the phrase of a certain kind. I call this the problem of distinguishing between standard and nonstandard models of computation. The successful drawing of this distinction guards Turing's 1936 analysis of computation against (...) a difficulty that has persistently been raised against it, and undercuts various objections that have been made to the computational theory of mind. (shrink)

I critically examine some provocative arguments that John Searle presents in his book The Rediscovery of Mind to support the claim that the syntactic states of a classical computational system are "observer relative" or "mind dependent" or otherwise less than fully and objectively real. I begin by explaining how this claim differs from Searle's earlier and more well-known claim that the physical states of a machine, including the syntactic states, are insufficient to determine its semantics. In contrast, his more recent (...) claim concerns the syntax, in particular, whether a machine actually has symbols to underlie its semantics. I then present and respond to a number of arguments that Searle offers to support this claim, including whether machine symbols are observer relative because the assignment of syntax is arbitrary, or linked to universal realizability, or linked to the sub-personal interpretive acts of a homunculus, or linked to a person's consciousness. I conclude that a realist about the computational model need not be troubled by such arguments. Their key premises need further support. (shrink)

The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...) states are individuated within computability theory and computer science. A secondary purpose is to show that existing arguments for the semantic view are defective. (shrink)

Some philosophers have conflated functionalism and computationalism. I reconstruct how this came about and uncover two assumptions that made the conflation possible. They are the assumptions that (i) psychological functional analyses are computational descriptions and (ii) everything may be described as performing computations. I argue that, if we want to improve our understanding of both the metaphysics of mental states and the functional relations between them, we should reject these assumptions. # 2004 Elsevier Ltd. All rights reserved.

The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach is that there is a natural domain of (...) human functioning that can be addressed exclusively in terms of a formal symbolic or algorithmic vocabulary or level of analysis. Much of the paper elaborates various conditions that need to be met if a literal view of mental activity as computation is to serve as the basis for explanatory theories. The coherence of such a view depends on there being a principled distinction between functions whose explanation requires that we posit internal representations and those that we can appropriately describe as merely instantiating causal physical or biological laws. In this paper the distinction is empirically grounded in a methodological criterion called the " cognitive impenetrability condition." Functions are said to be cognitively impenetrable if they cannot be influenced by such purely cognitive factors as goals, beliefs, inferences, tacit knowledge, and so on. Such a criterion makes it possible to empirically separate the fixed capacities of mind from the particular representations and algorithms used on specific occasions. In order for computational theories to avoid being ad hoc, they must deal effectively with the "degrees of freedom" problem by constraining the extent to which they can be arbitrarily adjusted post hoc to fit some particular set of observations. This in turn requires that the fixed architectural function and the algorithms be independently validated. It is argued that the architectural assumptions implicit in many contemporary models run afoul of the cognitive impenetrability condition, since the required fixed functions are demonstrably sensitive to tacit knowledge and goals. The paper concludes with some tactical suggestions for the development of computational cognitive theories. (shrink)

There are different ways to present a Presidential Address to the APA; the one I have chosen is simply to report on work that I am doing right now, on work in progress. I am going to present some of my further explorations into the computational model of the mind.\**.

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

This chapter describes a perspective on emotion, according to which emotions are: 1. Designed to function in a social context: an emotion is often an act of relationship reconfiguration brought about by delivering a social signal; 2. Forms of skillful engagement with the world which need not be mediated by conceptual thought; 3. Scaffolded by the environment, both synchronically in the unfolding of a particular emotional performance and diachronically, in the acquisition of an emotional repertoire; 4. Dynamically coupled to an (...) environment which both influences and is influenced by the unfolding of the emotion We draw heavily on ‘transactional’ accounts of emotion proposed by some contemporary psychologists. Although these authors do not, to our knowledge, conceive their work as a contribution to the ‘situationist’ literature that is the focus of this volume, we contend that their proposals constitute a fairly exact, affective parallel to situationist ideas about cognition. The primary aim of this chapter is to demonstrate that a situated approach to emotion already exists and is backed by a substantial experimental literature. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

Fodor and Pylyshyn's critique of connectionism has posed a challenge to connectionists: Adequately explain such nomological regularities as systematicity and productivity without postulating a "language of thought" (LOT). Some connectionists like Smolensky took the challenge very seriously, and attempted to meet it by developing models that were supposed to be non-classical. At the core of these attempts lies the claim that connectionist models can provide a representational system with a combinatorial syntax and processes sensitive to syntactic structure. They are not (...) implementation models because, it is claimed, the way they obtain syntax and structure sensitivity is not "concatenative," hence "radically different" from the way classicists handle them. In this paper, I offer an analysis of what it is to physically satisfy/realize a formal system. In this context, I examine the minimal truth-conditions of LOT Hypothesis. From my analysis it will follow that concatenative realization of formal systems is irrelevant to LOTH since the very notion of LOT is indifferent to such an implementation level issue as concatenation. I will conclude that to the extent to which they can explain the law-like cognitive regularities, a certain class of connectionist models proposed as radical alternatives to the classical LOT paradigm will in fact turn out to be LOT models, even though new and potentially very exciting ones. (shrink)

More than a decade ago, philosopher John Searle started a long-running controversy with his paper “Minds, Brains, and Programs” (Searle, 1980a), an attack on the ambitious claims of artificial intelligence (AI). With his now famous _Chinese Room_ argument, Searle claimed to show that despite the best efforts of AI researchers, a computer could never recreate such vital properties of human mentality as intentionality, subjectivity, and understanding. The AI research program is based on the underlying assumption that all important aspects of (...) human cognition may in principle be captured in a computational model. This assumption stems from the belief that beyond a certain level, implementational details are irrelevant to cognition. According to this belief, neurons, and biological wetware in general, have no preferred status as the substrate for a mind. As it happens, the best examples of minds we have at present have arisen from a carbon-based substrate, but this is due to constraints of evolution and possibly historical accidents, rather than to an absolute metaphysical necessity. As a result of this belief, many cognitive scientists have chosen to focus not on the biological substrate of the mind, but instead on the abstract causal structure_ _that the mind embodies (at an appropriate level of abstraction). The view that it is abstract causal structure that is essential to mentality has been an implicit assumption of the AI research program since Turing (1950), but was first articulated explicitly, in various forms, by Putnam (1960), Armstrong (1970) and Lewis (1970), and has become known as _functionalism_. From here, it is a very short step to _computationalism_, the view that computational structure is what is important in capturing the essence of mentality. This step follows from a belief that any abstract causal structure can be captured computationally: a belief made plausible by the Church–Turing Thesis, which articulates the power. (shrink)

The target article is an attempt to make some progress on the problem of color realism. Are objects colored? And what is the nature of the color properties? We defend the view that physical objects (for instance, tomatoes, radishes, and rubies) are colored, and that colors are physical properties, specifically types of reflectance. This is probably a minority opinion, at least among color scientists. Textbooks frequently claim that physical objects are not colored, and that the colors are "subjective" or "in (...) the mind." The article has two other purposes: first, to introduce an interdisciplinary audience to some distinctively philosophical tools that are useful in tackling the problem of color realism and, second, to clarify the various positions and central arguments in the debate. (shrink)

Imagine yourself sitting on your front porch, sipping your morning coffee and admiring the scene before you. You see trees, houses, people, automobiles; you see a cat running across the road, and a bee buzzing among the flowers. You see that the flowers are yellow, and blowing in the wind. You see that the people are moving about, many of them on bicycles. You see that the houses are painted different colors, mostly earth tones, and most are one-story but a (...) few are two-story. It is a beautiful morning. Thus the world interfaces with your mind through your senses. There is a strong intuition that we are not disconnected from the world. We and the other things we see around us are part of a continuous whole, and we have direct access to them through vision, touch, etc. However, the philosophical tradition tries to drive a wedge between us and the world by insisting that the information we get from perception is the result of inference from indirect evidence that is about how things look and feel to us. The philosophical problem of perception is then to explain what justifies these inferences. We will focus on visual perception. Figure one presents a crude diagram of the cognitive system of an agent capable of forming beliefs on the basis of visual perception. Cognition begins with the stimulation of the rods and cones on the retina. From that physical input, some kind of visual processing produces an introspectible visual image. In response to the production of the visual image, the cognizer forms beliefs about his or her surroundings. Some beliefs the perceptual beliefs are formed as direct responses to the visual input, and other beliefs are inferred from the perceptual beliefs. The perceptual beliefs are, at the very least, caused or causally influenced by having the image. This is signified by the dashed arrow marked with a large question mark. We will refer to this as the mystery link. Figure one makes it apparent that in order to fully understand how knowledge is based on perception, we need three different theories.. (shrink)

The Gestalt psychologists adopted a set of positions on mind-body issues that seem like an odd mix. They sought to combine a version of naturalism and physiological reductionism with an insistence on the reality of the phenomenal and the attribution of meanings to objects as natural characteristics. After reviewing basic positions in contemporary philosophy of mind, we examine the Gestalt position, characterizing it m terms of phenomenal realism and programmatic reductionism. We then distinguish Gestalt philosophy of mind from instrumentalism and (...) computational functionalism, and examine Gestalt attributions of meaning and value to perceived objects. Finally, we consider a metatheoretical moral from Gestalt theory, which commends the search for commensurate description of mental phenomena and their physiological counterparts. (shrink)

In an earlier paper, "Non-conceptual Content and the 'Space of Reasons'", I distinguished two forms of the view that perceptual content is non-conceptual, which I called the 'state view' and the 'content view'. On the latter, but not the former, perceptual states have a different kind of content than do cognitive states. Many have found it puzzling why anyone would want to make this claim and, indeed, what it might mean. This paper attempts to address these questions.

Certain of our concepts are innate, but many others are learned. Despite the plausibility of this claim, some have argued that the very idea of concept learning is incoherent. I present a conception of learning that sidesteps the arguments against the possibility of concept learning, and sketch several mechanisms that result in the generation of new primitive concepts. Given the rational considerations that motivate their deployment, I argue that these deserve to be called learning mechanisms. I conclude by replying to (...) the objections that these mechanisms cannot produce genuinely new content and cannot be part of genuinely cognitive explanations. (shrink)

What is a concept? Philosophers have given many different answers to this question, reflecting a wide variety of approaches to the study of mind and language. Nonetheless, at the most general level, there are two dominant frameworks in contemporary philosophy. One proposes that concepts are mental representations, while the other proposes that they are abstract objects. This paper looks at the differences between these two approaches, the prospects for combining them, and the issues that are involved in the dispute. We (...) argue that powerful motivations have been offered in support of both frameworks. This suggests the possibility of combining the two. Unlike Frege, we hold that the resulting position is perfectly coherent and well worth considering. Nonetheless, we argue that it should be rejected along with the view that concepts are abstract objects. (shrink)

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

The current orthodoxy on mental representation can be characterized in terms of three central ideas. The -rst is ontological, the second semantic, and the third methodological. The ontological tenet is that mental representation is a two-place relation holding between a representing state and a represented entity (object, event, state of a.airs). The semantic tenet is that the relation in question is probably information-theoretic at heart, perhaps augmented teleologically, functionally, or teleo-functionally to cope with di/cult cases. The methodological tenet is that (...) mental representations are posited solely on third-person explanatory grounds. In this paper, I argue that this picture of mental representation is satisfactory only as an account of mental representation at the sub-personal level. It is unsatisfactory, in a principled way, as an account of mental representation at the personal level. (shrink)

In her landmark book, Language, Thought, and Other Biological Categories (Millikan1984),1 Ruth Garrett Millikan utilizes the idea of a biological function to solve philosophical problems associated with the phenomena of language, thought, and meaning. Language and thought are activities of biological organisms, according to Millikan, and we should treat them as such when trying to answer related philosophical questions. Of special interest is Millikan’s treatment of intentionality. Here Millikan employs the notion of a biological function to explain what it is (...) for one thing in nature, a bee dance (43), for example, to be about another, in this case, the location of a nectar source. My concern in this paper is to understand whether Millikan’s account of intentionality adequately explains how humans achieve reference, in language or thought, to individuals and groups in their environment. In bringing her theory of intentional content to bear on human activities, Millikan focuses largely on natural language. Thus, in what follows, I begin by laying out the biology-based principles that underlie Millikan’s theory of content, then proceed with an explanation of how the theory is to apply to natural language. As it appears, Millikan’s account of how content is determined for natural language terms and sentences rests on the determinacy of intentional content at the psychological level. This leads me to take a careful look at what Millikan says about the content of mental representations, in hopes of finding a sufficient basis there for the application of Millikan’s theory of content to natural language. Ultimately, I conclude that Millikan’s theory faces a problem of vacuity. If we approach the theory as a theory of intentional content, intended to explain the nature of reference, the theory is lacking in an extremely important respect: Millikan explains how it could be one of the biological functions of a mental or natural language term to refer, without telling us precisely what in the natural order constitutes the reference relation.. (shrink)

This article responds to two unresolved and crucial problems of cognitive science: (1) What is actually accomplished by functions of the nervous system that we ordinarily describe in the intentional idiom? and (2) What makes the information processing involved in these functions semantic? It is argued that, contrary to the assumptions of many cognitive theorists, the computational approach does not provide coherent answers to these problems, and that a more promising start would be to fall back on mathematical communication theory (...) and, with the help of evolutionary biology and neurophysiology, to attempt a characterization of the adaptive processes involved in visual perception. Visual representations are explained as patterns of cortical activity that are enabled to focus on objects in the changing visual environment by constantly adjusting to maintain levels of mutual information between pattern and object that are adequate for continuing perceptual control. In these terms, the answer proposed to (1) is that the intentional functions of vision are those involved in the establishment and maintenance of such representations, and to (2) that semantic features are added to the information processes of vision with the focus on objects that these representations accomplish. The article concludes with proposals for extending this account of intentionality to the higher domains of conceptualization and reason, and with speculation about how semantic information-processing might be achieved in mechanical systems. (shrink)

The goal of philosophy of information is to understand what information is, how it operates, and how to put it to work. But unlike ‘information’ in the technical sense of information theory, what we are interested in is meaningful information. To understand the nature and dynamics of information in this sense we have to understand meaning. What we offer here are simple computational models that show emergence of meaning and information transfer in randomized arrays of neural nets. These we take (...) to be formal instantiations of a tradition of theories of meaning as use. What they offer, we propose, is a glimpse into the origin and dynamics of at least simple forms of meaning and information transfer as properties inherent in behavioral coordination across a community. (shrink)

Externalism about the mind holds that the explanation of our representational capacities requires appeal to mental states that are individuated by reference to features of the environment. Externalists claim that ‘narrow’ taxonomies cannot account for important features of psychological explanation. I argue that this claim is false, and offer a general argument for preferring narrow taxonomies in psychology.

Many philosophers hold that for various reasons there must be psychological laws governing beliefs and desires. One of the few serious examples that they offer is the _belief-desire law_, which states, roughly, that _ceteris paribus_ people do what they believe will satisfy their desires. This paper argues that, in fact, there is no such law. In particular, decision theory does not support the contention that there is such a law.

In a series of papers, Sperber provides the following analysis of the phenomenon of ill-understood belief (or 'quasi-belief', as I call it): (i) the quasi-believer has a validating meta-belief, to the effect that a certain representation is true; yet (ii) that representation does not give rise to a plain belief, because it is 'semi-propositional'. In this paper I discuss several aspects of this treatment. In particular, I deny that the representation accepted by the quasi-believer is semantically indeterminate, and I reject (...) Sperber's claim that quasi-belief is a credal attitude distinct from plain belief. (shrink)

The Language of Thought Hypothesis is often taken to have the fatal flaw that it generates an explanatory regress. The language of thought is invoked to explain certain features of natural language (e.g., that it is learned, understood, and is meaningful), but, according to the regress argument, the language of thought itself has these same features and hence no explanatory progress has been made. We argue that such arguments rely on the tacit assumption that the entire motivation for the language (...) of thought consists in explaining the explanandum that allegedly generates the regress. But this tacit assumption is simply false. The Language of Thought Hypothesis is a cogent view and one with considerable explanatory advantages. (shrink)

Many philosophers reject the Language of Thought Hypothesis (LOT) on the grounds that is leads to an explanatory regress problem. According to this line of argument, LOT is invoked to explain certain features of natural language, but the language of thought has the very same features and consequently no explanatory progress has been made. In an earlier paper (“Regress Arguments against the Language of Thought”, Analysis 57.1), we argued that this regress argument doesn’t work and that even proponents of LOT (...) have given the regress argument too much credit. In this paper, we extend our critique of the regress argument against LOT by responding to J. Knowles’s commentary of our earlier paper (in “The Language of Thought and Natural Language Understanding”, Analysis 58.4). (shrink)

In Section 5 of his interesting article, Goldman suggests that the consideration of imaginary cases can be valuable in the analysis of our psychological concepts. In particular, he argues that we can imagine a system that is isomorphic to us under any functional description, but which lacks qualitative mental states, such as pains and color sensations. Whether or not such a being is empirically possible, it certainly seems to be logically possible, or conceptually coherent. Goldman argues from this possibility to (...) the conclusion that our concepts of qualitative mental states cannot be analyzed entirely in functional terms. (shrink)

Byrne & Hilbert defend color realism, which assumes that: (a) colors are properties of objects; (b) these objects are physical; hence, (c) colors are physical properties. I accept (a), agree that in a certain sense (b) can be defended, but reject (c). Colors are properties of perceptual objects – which also have underlying physical properties – but they are not physical properties.

The rise of Bayesianism in cognitive science promises to shape the debate between nativists and empiricists into more productive forms—or so have claimed several philosophers and cognitive scientists. The present paper explicates this claim, distinguishing different ways of understanding it. After clarifying what is at stake in the controversy between nativists and empiricists, and what is involved in current Bayesian cognitive science, the paper argues that Bayesianism offers not a vindication of either nativism or empiricism, but one way to talk (...) precisely and transparently about the kinds of mechanisms and representations underlying the acquisition of psychological traits without a commitment to an innate language of thought. (shrink)

The semantic view of computation is the claim that semantic properties play an essential role in the individuation of physical computing systems such as laptops and brains. The main argument for the semantic view rests on the fact that some physical systems simultaneously implement different automata at the same time, in the same space, and even in the very same physical properties. Recently, several authors have challenged this argument. They accept the premise of simultaneous implementation but reject the semantic conclusion. (...) In this paper, I aim to explicate the semantic view and to address these objections. I first characterize the semantic view and distinguish it from other, closely related views. Then, I contend that the master argument for the semantic view survives the counter-arguments against it. One counter-argument is that computational individuation is not forced to choose between the implemented automata but rather always picks out a more basic computational structure. My response is that this move might undermine the notion of computational equivalence. Another counter-argument is that while computational individuation is forced to rely on extrinsic features, these features need not be semantic. My reply is that the semantic view better accounts for these extrinsic features than the proposed non-semantic alternatives. (shrink)

This paper argues that sociocultural accounts of learning fail to answer the key question about learning—how is it possible? Accordingly, we should adopt an individualist bootstrapping methodology in providing a theory of learning. Such a methodology takes seriously the idea that learning is staged and distinguishes between a non-comprehending engagement with things and a comprehending engagement. It suggests that, in the light of recent work in psychology with insights from Wittgenstein, there is rich scope for a bootstrapping account of learning. (...) The paper also argues that sociocultural approaches when pushed, either require some such bootstrapping account, or they collapse into an obscure Ficthean metaphysics in which individual abilities are ‘summoned into being’ by the attitudes of others. (shrink)