I argue that Frege Problems in thought are best modeled using graph-theoretic machinery; and that these problems can arise even when subjects associate all the same qualitative properties to the object they’re thinking of twice. I compare the proposed treatment to similar ideas by Heck, Ninan, Recanati, Kamp and Asher, Fodor, and others.

Western philosophy has a long-standing interest in the relationship between thought and language. This is not least because language use and our mental capacities are so central to our human self-conception, as well as to the ways in which we have tried to think about other beings. Retrospectively, it is possible to identify certain broad traditions in the philosophical study of thought and language, traditions which also have their representatives in psychology and linguistics. In this introduction I shall focus on (...) one such tradition, the one sometimes known as ‘lingualism ’, in so far as it bears on the papers brought together in this volume. (shrink)

Behaviorism and mentalism are commonly considered to be mutually exclusive and conjunctively exhaustive options for the psychological explanation of behavior. Behaviorism and mentalism do differ in their characterization of inner causes of behavior. However, I argue that they are not mutually exclusive on the grounds that they share important foundational assumptions, two of which are the notion of an innerouter split and the notion of control. I go on to argue that mentalism and behaviorism are not conjunctively exhaustive either, on (...) the grounds that dropping these common foundational assumptions results in a distinctively different framework for the explanation of behavior. This third alternative, which is briefly described, is a version of non-individualism. (shrink)

Moral particularism is a promising new approach which understands itself as a subchapter of holism in the theory of reasons. So particularism may be extended to other areas, such as metaphysics. One of the bases for this kind of move is elaborated by particularism itself as resultance, a strategy for providing the relevant basis that is opposed to various forms of generalism (the thin property of goodness is constituted by several thick properties, such as being good humoured, being pleasant; the (...) property of this being a table is constituted from properties of there being four legs, a plate, a certain arrangement). It is claimed that resultance or emergence needs a background structure in order to get off the ground. (shrink)

How much irrationality should we ascribe to human cognition? Psychological evidence suggests that people’s reasoning is largely inaccurate, but according to an evolutionary argument for rationality, we have good reasons to believe that this is not so. To solve the conflict between psychological evidence and EAR, commentators have usually put the blame either on the psychological evidence, arguing that inaccurate reasoning appears only in the context of lab studies, or on the premises of EAR, charged with not being in line (...) with the concepts and findings of evolutionary biology. I argue that Hammond’s distinction between two distinct criteria of rationality, namely coherence and correspondence, might shed new light on this apparent conflict. I show that EAR might be interpreted in two different ways, and that EAR and psychological evidence might in fact be both correct if they appeal to different criteria of accurate reasoning. Moreover, evolutionary considerations have been recently used not to oppose the existence of violations of norms of coherence but rather to explain it. (shrink)

Neurobiological models of language need a level of analysis that can account for the typical range of language phenomena. Because linguistically motivated models have been successful in explaining numerous language properties, it is premature to dismiss them as biologically irrelevant. Models attempting to unify neurobiology and linguistics need to be sensitive to both sources of evidence.

In this paper we defend structural representations, more specifically neural structural representation. We are not alone in this, many are currently engaged in this endeavor. The direction we take, however, diverges from the main road, a road paved by the mathematical theory of measure that, in the 1970s, established homomorphism as the way to map empirical domains of things in the world to the codomain of numbers. By adopting the mind as codomain, this mapping became a boon for all those (...) convinced that a representation system should bear similarities with what was being represented, but struggled to find a precise account of what such similarities mean. The euforia was brief, however, and soon homomorphism revealed itself to be affected by serious weaknesses, the primary one being that it included systems embarrassingly alien to representations. We find that the defense attempts that have followed, adopt strategies that share a common format: valid structural representations come as “homomorphism plus X”, with various “X”, provided in descriptive format only. Our alternative direction stems from the observation of the overlooked departure from homomorphism as used in the theory of measure and its later use in mental representations. In the former case, the codomain or the realm of numbers, is the most suited for developing theorems detailing the existence and uniqueness of homomorphism for a wide range of empirical domains. In the latter case, the codomain is the realm of the mind, possibly more vague and more ill-defined than the empirical domain itself. The time is ripe for articulating the mapping between represented domains and the mind in formal terms, by exploiting what is currently known about coding mechanisms in the brain. We provide a sketch of a possible development in this direction, one that adopts the theory of neural population coding as codomain. We will show that our framework is not only not in disagreement with the “plus X” proposals, but can lead to natural derivation of several of the “X”. (shrink)

The arguments of Fodor, Garret, Walker and Parkes [(1980) Against definitions, Cognition, 8, 263-367] are the source of widespread skepticism in cognitive science about lexical semantic structure. Whereas the thesis that lexical items, and the concepts they express, have decompositional structure (i.e. have significant constituents) was at one time "one of those ideas that hardly anybody [in the cognitive sciences] ever considers giving up" (p. 264), most researchers now believe that "[a]ll the evidence suggests that the classical [(decompositional)] view is (...) wrong as a general theory of concepts" [Smith, Medin & Rips (1984) A psychological approach to concepts: comments on Rey, Cognition, 17, 272], and cite Fodor et al. (1980) as "sounding the death knell for decompositional theories" [MacNamara & Miller (1989) Attributes of theories of meaning, Psychological Bulletin, 106, 360]. I argue that the prevailing skepticism is unmotivated by the arguments in Fodor et al. Fodor et al. misrepresent the form, function and scope of the decompositional hypothesis, and the procedures they employ to test for the psychological reality of definitions are flawed. I argue, further, that decompositional explanations of the phenomena they consider are preferable to their primitivist alternatives, and, hence, that there is prima facie reason to accept them as evidence for the existence of decompositional structure. Cognitive scientists would, therefore, do well to revert to their former commitment to the decompositional hypothesis. (shrink)

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

The Church–Turing Thesis (CTT) is often employed in arguments for computationalism. I scrutinize the most prominent of such arguments in light of recent work on CTT and argue that they are unsound. Although CTT does nothing to support computationalism, it is not irrelevant to it. By eliminating misunderstandings about the relationship between CTT and computationalism, we deepen our appreciation of computationalism as an empirical hypothesis.

Before embarking upon the project of reformulating psychoanalysis in the 'scientific' terminology of cognitive science, we should first clearly define what psychoanalysis is about and what it is not about. Cognitive science is based upon a functionalistic philosophy of the mind. As a consequence such a project would require a functionalistic core theory of psychoanalysis. But Freud's claim of the therapeutic effect of psychoanalysis, attained through the rendering conscious of what is unconscious or the making personal of what is experienced (...) by the neurotic patient as impersonal, cannot be explained by a functionalistic theory of the mind We examine Freud's claim and conclude that there ought to be a philosophy of qualia at the core of psychoanalysis. (shrink)

This paper addresses the questions concerningthe relationship between scientific andcognitive processes. The fact that both,science and cognition, aim at acquiring somekind of knowledge or representationabout the world is the key for establishing alink between these two domains. It turns outthat the constructivist frameworkrepresents an adequate epistemologicalfoundation for this undertaking, as its focusof interest is on the (constructive)relationship between the world and itsrepresentation. More specifically, it will beshown how cognitive processes and their primaryconcern to construct a representation of theenvironment and to (...) generate functionallyfitting behavior can act as the basis forembedding the activities and dynamics of theprocess of science in them by making use ofconstructivist concepts, such as functionalfitness, structure determinedness, etc.Cognitive science and artificiallife provide the conceptual framework of representational spaces and their interactionbetween each other and with the environmentenabling us to establish this link betweencognitive processes and thedevelopment/dynamics of scientific theories.The concepts of activation, synaptic weight,and genetic (representational) spaces arepowerful tools which can be used asexplanatory vehiclesfor a cognitivefoundation of science, more specifically forthe context of discovery (i.e., thedevelopment, construction, and dynamics ofscientific theories and paradigms).Representational spaces do not only offer us abetter understanding of embedding science incognition, but also show, how theconstructivist framework, both, can act as anadequate epistemological foundation for theseprocesses and can be instantiated by theserepresentational concepts from cognitivescience. The final part of this paper addresses somemore fundamental questions concerning thepositivistic and constructivist understandingof science and human cognition. Among otherthings it is asked, whether a purelyfunctionalist and quantitative view of theworld aiming almost exclusively at itsprediction and control is really satisfying forour intellect (having the goal of achieving aprofound understanding of reality). (shrink)

This article explores some of the philosophical implications of the Bayesian modeling paradigm. In particular, it focuses on the ramifications of the fact that Bayesian models pre‐specify an inbuilt hypothesis space. To what extent does this pre‐specification correspond to simply ‘‘building the solution in''? I argue that any learner must have a built‐in hypothesis space in precisely the same sense that Bayesian models have one. This has implications for the nature of learning, Fodor's puzzle of concept acquisition, and the role (...) of modeling in cognitive science. (shrink)

Observations from philosophy and psychology heavily favor the Empiricist tenet that many lexical concepts are learned. However, many observations also heavily favor the Nativist tenet that such concepts are representationally atomic. Fodor Representations: Philosophical essays on the foundations of cognitive science, 1981, LOT2: The language of thought revisited, 2008) has famously argued that representationally atomic concepts cannot be learned, at least not learned by hypothesis formation and testing. Concept theorists who want to preserve observations about concept learning have developed acquisition (...) models on which the acquired concepts are either non-atomic or are acquired by a process that doesn’t involve hypothesis formation and testing. I offer a model, Baptizing Meanings for Concepts, in which representationally atomic concepts are learned by hypothesis formation and testing. The concepts are learned by the agent’s hypothesizing the existence of a latent/hidden/imperceptible property in objects to explain the objects’ perceptible similarities. Once a hidden property is hypothesized, a new atomic mental name is assigned to it, and this atomic name becomes the concept. Any connections between the name and the representations involved in linking the name to its referent are stored as contingent. Further experience may give the agent reason to revise its hypotheses about latent properties as explanations for its observations. I discuss a software robot implementation of the BMC process that uses a Bayesian learning network. The implementation provides an existence proof of the possibility of learning representationally atomic concepts by hypothesis formation and testing. (shrink)

One of the principal tasks Dennett sets himself in Consciousness Explained is to demolish the Cartesian theater model of phenomenal consciousness, which in its contemporary garb takes the form of Cartesian materialism: the idea that conscious experience is a process of presentation realized in the physical materials of the brain. The now standard response to Dennett is that, in focusing on Cartesian materialism, he attacks an impossibly naive account of consciousness held by no one currently working in cognitive science or (...) the philosophy of mind. Our response is quite different. We believe that, once properly formulated, Cartesian materialism is no straw man. Rather, it is an attractive hypothesis about the relationship between the computational architecture of the brain and phenomenal consciousness, and hence one that is worthy of further exploration. Consequently, our primary aim in this paper is to defend Cartesian materialism from Dennett’s assault. We do this by showing that Dennett’s argument against this position is founded on an implicit assumption (about the relationship between phenomenal experience and information coding in the brain), which while valid in the context of classical cognitive science, is not forced on connectionism. (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)

When it comes to applying computational theory to the problem of phenomenal consciousness, cognitive scientists appear to face a dilemma. The only strategy that seems to be available is one that explains consciousness in terms of special kinds of computational processes. But such theories, while they dominate the field, have counter-intuitive consequences; in particular, they force one to accept that phenomenal experience is composed of information processing effects. For cognitive scientists, therefore, it seems to come down to a choice between (...) a counter-intuitive theory or no theory at all. We offer a way out of this dilemma. We argue that the computational theory of mind doesn't force cognitive scientists to explain consciousness in terms of computational processes, as there is an alternative strategy available: one that focuses on the representational vehicles that encode information in the brain. This alternative approach to consciousness allows us to do justice to the standard intuitions about phenomenal experience, yet remain within the confines of cognitive science. (shrink)

Theses claiming a constitutive or necessary role for belief-desire pairs in the rationalizing, motivation or explanation of action, are generally known as Humean. The main purpose of this short paper is clearly to present the basic versions of Humeanism and lay bare their commitments and interrelations in preparation for a short general introduction to the debate over belief-desire explanation of action. After this, some influential arguments for and against a Humean account of action explanation are briefly discussed.

Because Müiller fails to distinguish between two senses of the term “autonomy,” there is a danger that his results will be misinterpreted by both linguists and neuroscientists. Although he may very well have been successful in refuting one sense of autonomy, he may actually have helped to provide an explanation for the correctness of autonomy in its other sense.

Having, in previous papers, distinguished at least three forms of consciousness , I now further examine their differences. This examination has some surprising results. Having argued that neither C1 nor C2 is a phenomenological state?and so different from CN?I now show that CN itself is best thought of as a subclass of a larger state . CS is the set of image?representation states. CN is that set of CS states that we are also C2 about. I argue that CN states (...) should be considered a subset of CS states because they share with other CS states imagistic representational powers as opposed to the sentential ones of C1 and C2. And I argue that there are good reasons to consider any state which utilises imagistic representation as a sensation. I then show that the notion of an unconscious sensation makes sense if we think of it as a CS state that is not C2. More radically, I conclude that either it makes sense to say that there are unfelt sensations or there are felt sensations we are not conscious about. While there are good reasons for saying one or the other of these surprising things, I argue that the second, more radical sounding, alternative is actually better motivated?and not quite so surprising as it sounds. (shrink)