A survey of contemporary philosophical and scientific literatures reveals that different authors employ the term ‘heuristic’ in ways that deviate from, and are sometimes inconsistent with, one another. Given its widespread use in philosophy and cognitive science generally, it is striking that there appears to be little concern for a clear account of what phenomena heuristics pick out or refer to. In response, I consider several accounts of ‘heuristic’, and I draw a number of distinctions between different sorts of heuristics (...) in order to make sense of various research programmes. I then develop a working characterization of ‘heuristic’ which is shown to be coherent and robust enough to serve as a kind within philosophy and cognitive science broadly. My intent is not to pursue a unified account of ‘heuristic’, but to highlight some features of certain kinds of heuristics that are important for theorizing about cognition in order to proceed with a science of the mind/brain. 1 Why We Need an Appropriate Characterization of ‘Heuristic’2 Inadequate Definitions2.1 A positive attempt2.2 Heuristics versus guaranteed correct outcomes3 A Taxonomy of Heuristics3.1 Stimulus-driven versus heuristic3.2 Perceptual versus cognitive heuristics3.3 Computational versus cognitive heuristics3.4 Methodological versus inferential heuristics3.5 Summary of distinctions4 Characterizing Cognitive Heuristics4.1 Heuristics as rules of thumb4.2 Beyond rules of thumb: exploiting information5 Concluding Remarks. (shrink)

According to intentionalism, phenomenal properties are identical to, supervenient on, or determined by representational properties. Intentionalism faces a special challenge when it comes to accounting for the phenomenal character of moods. First, it seems that no intentionalist treatment of moods can capture their apparently undirected phenomenology. Second, it seems that even if we can come up with a viable intentionalist account of moods, we would not be able to motivate it in some of the same kinds of ways that intentionalism (...) about other kinds of states can be motivated. In this article, I respond to both challenges: First, I propose a novel intentionalist treatment of moods on which they represent unbound affective properties. Then, I argue that this view is indirectly supported by the same kinds of considerations that directly support intentionalism about other mental states. (shrink)

Talk of linguistic universals has given cognitive scientists the impression that languages are all built to a common pattern. In fact, there are vanishingly few universals of language in the direct sense that all languages exhibit them. Instead, diversity can be found at almost every level of linguistic organization. This fundamentally changes the object of enquiry from a cognitive science perspective. This target article summarizes decades of cross-linguistic work by typologists and descriptive linguists, showing just how few and unprofound the (...) universal characteristics of language are, once we honestly confront the diversity offered to us by the world's 6,000 to 8,000 languages. After surveying the various uses of “universal,” we illustrate the ways languages vary radically in sound, meaning, and syntactic organization, and then we examine in more detail the core grammatical machinery of recursion, constituency, and grammatical relations. Although there are significant recurrent patterns in organization, these are better explained as stable engineering solutions satisfying multiple design constraints, reflecting both cultural-historical factors and the constraints of human cognition.Linguistic diversity then becomes the crucial datum for cognitive science: we are the only species with a communication system that is fundamentally variable at all levels. Recognizing the true extent of structural diversity in human language opens up exciting new research directions for cognitive scientists, offering thousands of different natural experiments given by different languages, with new opportunities for dialogue with biological paradigms concerned with change and diversity, and confronting us with the extraordinary plasticity of the highest human skills. (shrink)

Our response takes advantage of the wide-ranging commentary to clarify some aspects of our original proposal and augment others. We argue against the generative critics of our coevolutionary program for the language sciences, defend the use of close-to-surface models as minimizing cross-linguistic data distortion, and stress the growing role of stochastic simulations in making generalized historical accounts testable. These methods lead the search for general principles away from idealized representations and towards selective processes. Putting cultural evolution central in understanding language (...) diversity makes learning fundamental in the cognition of language: increasingly powerful models of general learning, paired with channelled caregiver input, seem set to manage language acquisition without recourse to any innate “universal grammar.” Understanding why human language has no clear parallels in the animal world requires a cross-species perspective: crucial ingredients are vocal learning (for which there are clear non-primate parallels) and an intention-attributing cognitive infrastructure that provides a universal base for language evolution. We conclude by situating linguistic diversity within a broader trend towards understanding human cognition through the study of variation in, for example, human genetics, neurocognition, and psycholinguistic processing. (shrink)

On a traditional or default view of the grasping or understanding of a singular proposition by an individual, it is assumed to be a unitary or holistic activity. However, naturalistic views of cognition plausibly could analyze propositional thinking in terms of more than one distinctive functional stage of cognitive processing, suggesting at least the potential legitimacy of a non-unitary analysis of propositional grasping. We outline a novel dual-component view of this kind, and show that it is well supported by current (...) cognitive science research. (shrink)

Behaviourism is the view that preferences, beliefs, and other mental states in social-scientific theories are nothing but constructs re-describing people's behaviour. Mentalism is the view that they capture real phenomena, on a par with the unobservables in science, such as electrons and electromagnetic fields. While behaviourism has gone out of fashion in psychology, it remains influential in economics, especially in ‘revealed preference’ theory. We defend mentalism in economics, construed as a positive science, and show that it fits best scientific practice. (...) We distinguish mentalism from, and reject, the radical neuroeconomic view that behaviour should be explained in terms of brain processes, as distinct from mental states. (shrink)

I develop a view of the common factor between subjectively indistinguishable perceptions and hallucinations that avoids analyzing experiences as involving awareness relations to abstract entities, sense-data, or any other peculiar entities. The main thesis is that hallucinating subjects employ concepts (or analogous nonconceptual structures), namely the very same concepts that in a subjectively indistinguishable perception are employed as a consequence of being related to external, mind-independent objects or property-instances. These concepts and nonconceptual structures are identified with modes of presentation types. (...) Since a hallucinating subject is not related to any such objects or property-instances, the concepts she employs remain empty. I argue that the phenomenology of hallucinations and perceptions can be identified with employing concepts and analogous nonconceptual structures. By doing so, I defend an ontologically minimalist view of the phenomenology of experience that (1) vindicates Aristotelianism about types and (2) amounts to a naturalized view of the phenomenology of experience. (shrink)

The lack of consensus on how to characterize humans’ capacity for belief reasoning has been brought into sharp focus by recent research. Children fail critical tests of belief reasoning before 3 to 4 years (Wellman, Cross, & Watson, 2001; Wimmer & Perner, 1983), yet infants apparently pass false belief tasks at 13 or 15 months (Onishi & Baillargeon, 2005; Surian, Caldi, & Sperber, 2007). Non-human animals also fail critical tests of belief reasoning but can show very complex social behaviour (e.g., (...) Call & Tomasello, 2005). Fluent social interaction in adult humans implies efficient processing of beliefs, yet direct tests suggest that belief reasoning is cognitively demanding, even for adults (e.g., Apperly, Samson & Humphreys, 2005). We interpret these findings by drawing an analogy with the domain of number cognition, where similarly contrasting results have been observed. We propose that the success of infants and non-human animals on some belief reasoning tasks may be best explained by a cognitively efficient but inflexible capacity for tracking belief-like states. In humans this capacity persists in parallel with later-developing, more flexible but more cognitively demanding theory of mind abilities. (shrink)

Our target article argued that a genetically specified Universal Grammar (UG), capturing arbitrary properties of languages, is not tenable on evolutionary grounds, and that the close fit between language and language learners arises because language is shaped by the brain, rather than the reverse. Few commentaries defend a genetically specified UG. Some commentators argue that we underestimate the importance of processes of cultural transmission; some propose additional cognitive and brain mechanisms that may constrain language and perhaps differentiate humans from nonhuman (...) primates; and others argue that we overstate or understate the case against co-evolution of language genes. In engaging with these issues, we suggest that a new synthesis concerning the relationship between brains, genes, and language may be emerging. (shrink)

This article deals with the relationship between language and thought, focusing on the question of whether language can be a vehicle of thought, as, for example, Peter Carruthers has claimed. We develop and examine a powerful argument—the "argument from explicitness"—against this cognitive role of language. The premises of the argument are just two: (1) the vehicle of thought has to be explicit, and (2) natural languages are not explicit. We explain what these simple premises mean and why we should believe (...) they are true. Finally, we argue that even though the argument from explicitness shows that natural language cannot be a vehicle of thought, there is a cognitive function for language. (shrink)

This essay is a sustained attempt to bring new light to some of the perennial problems in philosophy of mind surrounding phenomenal consciousness and introspection through developing an account of sensory and phenomenal concepts. Building on the information-theoretic framework of Dretske (1981), we present an informational psychosemantics as it applies to what we call sensory concepts, concepts that apply, roughly, to so-called secondary qualities of objects. We show that these concepts have a special informational character and semantic structure that closely (...) tie them to the brain states realizing conscious qualitative experiences. We then develop an account of introspection which exploits this special nature of sensory concepts. The result is a new class of concepts, which, following recent terminology, we call phenomenal concepts: these concepts refer to phenomenal experience itself and are the vehicles used in introspection. On our account, the connection between sensory and phenomenal concepts is very tight: it consists in different semantic uses of the same cognitive structures underlying the sensory concepts, such as the concept of red. Contrary to widespread opinion, we show that information theory contains all the resources to satisfy internalist intuitions about phenomenal consciousness, while not offending externalist ones. A consequence of this account is that it explains and predicts the so-called conceivability arguments against physicalism on the basis of the special nature of sensory and phenomenal concepts. Thus we not only show why physicalism is not threatened by such arguments, but also demonstrate its strength in virtue of its ability to predict and explain away such arguments in a principled way. However, we take the main contribution of this work to be what it provides in addition to a response to those conceivability arguments, namely, a substantive account of the interface between sensory and conceptual systems and the mechanisms of introspection as based on the special nature of the information flow between them. (shrink)

Humans and other animals are able not only to coordinate their actions with their current sensorimotor state, but also to imagine, plan and act in view of the future, and to realize distal goals. In this paper we discuss whether or not their future-oriented conducts imply (future-oriented) representations. We illustrate the role played by anticipatory mechanisms in natural and artificial agents, and we propose a notion of representation that is grounded in the agent’s predictive capabilities. Therefore, we argue that the (...) ability that characterizes and defines a true cognitive mind, as opposed to a merely adaptive system, is that of building representations of the non-existent, of what is not currently (yet) true or perceivable, of what is desired. A real mental activity begins when the organism is able to endogenously (i.e. not as the consequence of current perceptual stimuli) produce an internal representation of the world in order to select and guide its conduct goal-directed: the mind serves to coordinate with the future. (shrink)

What would it be like to have never learned English, but instead only to know Hopi, Mandarin Chinese, or American Sign Language? Would that change the way you think? Imagine entirely losing your language, as the result of stroke or trauma. You are aphasic, unable to speak or listen, read or write. What would your thoughts now be like? As the most extreme case, imagine having been raised without any language at all, as a wild child. What—if anything—would it be (...) like to be such a person? Could you be smart; could you reminisce about the past, plan the future? (shrink)

We provide a taxonomy of the two most important debates in the philosophy of the cognitive and neural sciences. The first debate is over methodological individualism: is the object of the cognitive and neural sciences the brain, the whole animal, or the animal--environment system? The second is over explanatory style: should explanation in cognitive and neural science be reductionist-mechanistic, inter-level mechanistic, or dynamical? After setting out the debates, we discuss the ways in which they are interconnected. Finally, we make some (...) recommendations that we hope will help philosophers interested in the cognitive and neural sciences to avoid dead ends. (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.

It is generally accepted that there is something special about reasoning by using mental images. The question of how it is special, however, has never been satisfactorily spelled out, despite more than thirty years of research in the post-behaviorist tradition. This article considers some of the general motivation for the assumption that entertaining mental images involves inspecting a picture-like object. It sets out a distinction between phenomena attributable to the nature of mind to what is called the cognitive architecture, and (...) ones that are attributable to tacit knowledge used to simulate what would happen in a visual situation. With this distinction in mind, the paper then considers in detail the widely held assumption that in some important sense images are spatially displayed or are depictive, and that examining images uses the same mechanisms that are deployed in visual perception. I argue that the assumption of the spatial or depictive nature of images is only explanatory if taken literally, as a claim about how images are physically instantiated in the brain, and that the literal view fails for a number of empirical reasons – for example, because of the cognitive penetrability of the phenomena cited in its favor. Similarly, while it is arguably the case that imagery and vision involve some of the same mechanisms, this tells us very little about the nature of mental imagery and does not support claims about the pictorial nature of mental images. Finally, I consider whether recent neuroscience evidence clarifies the debate over the nature of mental images. I claim that when such questions as whether images are depictive or spatial are formulated more clearly, the evidence does not provide support for the picture-theory over a symbol-structure theory of mental imagery. Even if all the empirical claims were true, they do not warrant the conclusion that many people have drawn from them: that mental images are depictive or are displayed in some (possibly cortical) space. Such a conclusion is incompatible with what is known about how images function in thought. We are then left with the provisional counterintuitive conclusion that the available evidence does not support rejection of what I call the “null hypothesis”; namely, that reasoning with mental images involves the same form of representation and the same processes as that of reasoning in general, except that the content or subject matter of thoughts experienced as images includes information about how things would look. (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)

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)

In this paper, I argue that theories of perception that appeal to Helmholtz’s idea of unconscious inference (“Helmholtzian” theories) should be taken literally, i.e. that the inferences appealed to in such theories are inferences in the full sense of the term, as employed elsewhere in philosophy and in ordinary discourse. -/- In the course of the argument, I consider constraints on inference based on the idea that inference is a deliberate acton, and on the idea that inferences depend on the (...) syntactic structure of representations. I argue that inference is a personal-level but sometimes unconscious process that cannot in general be distinguished from association on the basis of the structures of the representations over which it’s defined. I also critique arguments against representationalist interpretations of Helmholtzian theories, and argue against the view that perceptual inference is encapsulated in a module. (shrink)

I present a paradoxical combination of desires. I show why it's paradoxical, and consider ways of responding. The paradox saddles us with an unappealing trilemma: either we reject the possibility of the case by placing surprising restrictions on what we can desire, or we deny plausibly constitutive principles linking desires to the conditions under which they are satisfied, or we revise some bit of classical logic. I argue that denying the possibility of the case is unmotivated on any reasonable way (...) of thinking about mental content, and rejecting those desire-satisfaction principles leads to revenge paradoxes. So the best response is a non-classical one, according to which certain desires are neither determinately satisfied nor determinately not satisfied. Thus, theorizing about paradoxical propositional attitudes helps constrain the space of possibilities for adequate solutions to semantic paradoxes more generally. (shrink)

This is a reminiscence and short biographical sketch of the late philosopher and cognitive scientist Jerry Fodor. It includes a summary of his main proposals about the mind: his “Language of Thought” hypothesis; his rejection of analyticity and conceptual role semantics; his “mad dog nativism”; his proposal of mental modules and—by contrast—his skepticism about a computational theory of central cognition; his anti‐reductionist, but still physicalist, views about psychology; and, lastly, his attacks on selectionism. I conclude with some discussion of his (...) idiosyncratic style and of his aesthetic and other interests. An appendix provides some memorable quotes. (shrink)

Perceptual systems respond to proximal stimuli by forming mental representations of distal stimuli. A central goal for the philosophy of perception is to characterize the representations delivered by perceptual systems. It may be that all perceptual representations are in some way proprietarily perceptual and differ from the representational format of thought (Dretske 1981; Carey 2009; Burge 2010; Block ms.). Or it may instead be that perception and cognition always trade in the same code (Prinz 2002; Pylyshyn 2003). This paper rejects (...) both approaches in favor of perceptual pluralism, the thesis that perception delivers a multiplicity of representational formats, some proprietary and some shared with cognition. The argument for perceptual pluralism marshals a wide array of empirical evidence in favor of iconic (i.e., image-like, analog) representations in perception as well as discursive (i.e., language-like, digital) perceptual object representations. (shrink)

This paper engages critically with anti-representationalist arguments pressed by prominent enactivists and their allies. The arguments in question are meant to show that the “as-such” and “job-description” problems constitute insurmountable challenges to causal-informational theories of mental content. In response to these challenges, a positive account of what makes a physical or computational structure a mental representation is proposed; the positive account is inspired partly by Dretske’s views about content and partly by the role of mental representations in contemporary cognitive scientific (...) modeling. (shrink)

Gleitman and Trueswell’s “The easy words” forms a pair with their earlier paper, “Hard words,” completing a circle in which the authors ask how “easy” words (e.g., concrete nouns) are learned. They take up the hypothesis of “cross‐situational learning,” and argue that accumulating observations actually hinders learning if the mechanism requires holding all exemplars in memory over time. They present an alternative hypothesis, “Propose but Verify,” wherein people use one‐trial learning to confirm or disconfirm their current hypothesis—a mechanism distinctly different (...) from cross‐situational learning. (shrink)

In recent years, many philosophers and scientists have argued or accepted that it is impossible to learn primitive sensory concepts like “blue” and “red”. This paper defends a more qualified picture. I try to show that some received characterisations of “learning” are nonequivalent and point towards different learning-nonlearning distinctions. And, on some ways of specifying such a distinction, it might be correct that we do not and cannot “learn” a concept of blue. But on other ways of specifying such a (...) distinction, we can and do sometimes “learn” a concept of blue from experiences of blue. The latter part of the argument connects with some traditional “abstractionist” views, and I defend the present claims in view of some widely circulated concerns about “abstracting” concepts from experience. I close with some reflections on how one might, in view of all this, think about “the learning-nonlearning distinction”. (shrink)

Whilst much has been said about the implications of predictive processing for our scientific understanding of cognition, there has been comparatively little discussion of how this new paradigm fits with our everyday understanding of the mind, i.e. folk psychology. This paper aims to assess the relationship between folk psychology and predictive processing, which will first require making a distinction between two ways of understanding folk psychology: as propositional attitude psychology and as a broader folk psychological discourse. It will be argued (...) that folk psychology in this broader sense is compatible with predictive processing, despite the fact that there is an apparent incompatibility between predictive processing and a literalist interpretation of propositional attitude psychology. The distinction between these two kinds of folk psychology allows us to accept that our scientific usage of folk concepts requires revision, whilst rejecting the suggestion that we should eliminate folk psychology entirely. (shrink)

Nativists about theory of mind have typically explained why children below the age of four fail the false belief task by appealing to the demands that these tasks place on children’s developing executive abilities. However, this appeal to executive functioning cannot explain a wide range of evidence showing that social and linguistic factors also affect when children pass this task. In this paper, I present a revised nativist proposal about theory of mind development that is able to accommodate these findings, (...) which I call the pragmatic development account. According to this proposal, we can gain a better understanding of the shift in children’s performance on standard false-belief tasks around four years of age by considering how children’s experiences with the pragmatics of belief discourse affect the way they interpret the task. (shrink)

Empirical discussions of mental representation appeal to a wide variety of representational kinds. Some of these kinds, such as the sentential representations underlying language use and the pictorial representations of visual imagery, are thoroughly familiar to philosophers. Others have received almost no philosophical attention at all. Included in this latter category are analogue magnitude representations, which enable a wide range of organisms to primitively represent spatial, temporal, numerical, and related magnitudes. This article aims to introduce analogue magnitude representations to a (...) philosophical audience by rehearsing empirical evidence for their existence and analysing their format, their content, and the computations they support. 1 Background1.1 Evidence of analogue magnitude representations1.2 Weber’s law1.3 Scepticism about analogue magnitude representations2 Format2.1 Carey’s analogy2.2 Neural realization2.3 Analogue representation2.4 Analogue magnitude representation components3 Content3.1 Do analogue magnitude representations have representational content?3.2 What do analogue magnitude representations represent?3.3 What content types do analogue magnitude representations have?4 Computations4.1 Arithmetic computation4.2 Practical deliberation5 Conclusion. (shrink)

I argue that any account of perceptual experience should satisfy the following two desiderata. First, it should account for the particularity of perceptual experience, that is, it should account for the mind-independent object of an experience making a difference to individuating the experience. Second, it should explain the possibility that perceptual relations to distinct environments could yield subjectively indistinguishable experiences. Relational views of perceptual experience can easily satisfy the first but not the second desideratum. Representational views can easily satisfy the (...) second but not the first desideratum. I argue that to satisfy both desiderata perceptual experience is best conceived of as fundamentally both relational and representational. I develop a view of perceptual experience that synthesizes the virtues of relationalism and representationalism, by arguing that perceptual content is constituted by potentially gappy de re modes of presentation. (shrink)

The paper considers our ordinary mentalistic discourse in relation to what we should expect from any genuine science of the mind. A meta-scientific eliminativism is commended and distinguished from the more familiar eliminativism of Skinner and the Churchlands. Meta-scientific eliminativism views folk psychology qua folksy as unsuited to offer insight into the structure of cognition, although it might otherwise be indispensable for our social commerce and self-understanding. This position flows from a general thesis that scientific advance is marked by an (...) eschewal of folk understanding. The latter half of the paper argues that, contrary to the received view, Chomsky's review of Skinner offers not just an argument against Skinner's eliminativism, but, more centrally, one in favour of the second eliminativism. (shrink)

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.

I offer a new argument for the elimination of ‘beliefs’ from cognitive science based on Wimsatt’s concept of robustness and a related concept of fragility. Theoretical entities are robust if multiple independent means of measurement produce invariant results in detecting them. Theoretical entities are fragile when multiple independent means of detecting them produce highly variant results. I argue that sufficiently fragile theoretical entities do not exist. Recent studies in psychology show radical variance between what self-report and non-verbal behaviour indicate about (...) participants’ beliefs. This is evidence that ‘belief’ is fragile, and is thus a strong candidate for elimination. 1 Introduction2 Robustness and Fragility2.1 A historical example of robustness2.2 Fragility and elimination3 The Received View4 Evidence for the Fragility of Belief4.1 Contamination and fragility4.2 Implicit association tests and fragility5 Attempts to Preserve the Belief Category for Cognitive Science5.1 Beliefs and aliefs5.2 Contradictory beliefs5.3 In-between beliefs and the unity assumption5.4 Belief sub-classes5.5 Self-deception6 Alternative Mental States7 Conclusion. (shrink)

This article presents a formal theory of robot perception as a form of abduction. The theory pins down the process whereby low‐level sensor data is transformed into a symbolic representation of the external world, drawing together aspects such as incompleteness, top‐down information flow, active perception, attention, and sensor fusion in a unifying framework. In addition, a number of themes are identified that are common to both the engineer concerned with developing a rigorous theory of perception, such as the one on (...) offer here, and the philosopher of mind who is exercised by questions relating to mental representation and intentionality. (shrink)

This paper deals with the question: what are the key requirements for a physical system to perform digital computation? Time and again cognitive scientists are quick to employ the notion of computation simpliciter when asserting basically that cognitive activities are computational. They employ this notion as if there was or is a consensus on just what it takes for a physical system to perform computation, and in particular digital computation. Some cognitive scientists in referring to digital computation simply adhere to (...) Turing’s notion of computability . Classical computability theory studies what functions on the natural numbers are computable and what mathematical problems are undecidable. Whilst a mathematical formalism of computability may perform a methodological function of evaluating computational theories of certain cognitive capacities, concrete computation in physical systems seems to be required for explaining cognition as an embodied phenomenon . There are many non-equivalent accounts of digital computation in physical systems. I examine only a handful of those in this paper: (1) Turing’s account ; (2) The triviality “account”; (3) Reconstructing Smith’s account of participatory computation ; (4) The Algorithm Execution account . My goal in this paper is twofold. First, it is to identify and clarify some of the underlying key requirements mandated by these accounts. I argue that these differing requirements justify a demand that one commits to a particular account when employing the notion of computation in regard to physical systems. Second, it is to argue that despite the informative role that mathematical formalisms of computability may play in cognitive science, they do not specify the relationship between abstract and concrete computation. (shrink)

The tuning-fork model of human social cognition, based on the discovery of mirror neurons (MNs) in the ventral premotor cortex of monkeys, involves the four following assumptions: (1) mirroring processes are processes of resonance or simulation. (2) They can be motor or non-motor. (3) Processes of motor mirroring (or action-mirroring), exemplified by the activity of MNs, constitute instances of third-person mindreading, whereby an observer represents the agent's intention. (4) Non-motor mirroring processes enable humans to represent others' emotions. After questioning all (...) four assumptions, I point out that MNs in an observer's brain could not synchronically resonate with MNs in an agent's brain unless they discharged in a single brain in two distinct tasks at different times. Finally, I sketch a conceptualist alternative to the resonance model according to which a brain mechanism active in both the execution and the perception of e.g., the act of grasping is the neural basis of the concept of e.g., grasping. (shrink)

The cognitive neuropsychological understanding of a cognitive system is roughly that of a ‘mental organ’, which is independent of other systems, specializes in some cognitive task, and exhibits a certain kind of internal cohesiveness. This is all quite vague, and I try to make it more precise. A more precise understanding of cognitive systems will make it possible to articulate in some detail an alternative to the Fodorian doctrine of modularity (since not all cognitive systems are modules), but it will (...) also provide a better understanding of what a module is (since all modules are cognitive systems). (shrink)

Faced with realist-resistant sciences and the no-nonsense attitude of the times realism has moved away from the rather grandiose program that had traditionally been characteristic of its school. The objective of the shift seems to be to protect some doctrine still worthy of the "realist" name. The strategy is to relocate the school to where conditions seem optimal for its defense, and then to insinuate that the case for such a " piecemeal realism" could be made elsewhere too, were there (...) but world enough and time. The burden of this paper is to examine this piecemeal approach and to show why, despite the relocation, it cannot escape the difficulties of its grander cousins. For that purpose I begin with some brief historical reminders, and with a quick review of the state of the argument before realism went to pieces. This will help us see what has been abandoned in realism's flight, and what baggage still remains. (shrink)

Many think that the perceptual theory known as “conceptualism” cannot honor a common and intuitive constraint on concept acquisition—that we gain the initial power to deploy primitive concepts through experience. Their argument is: if experience involves the deployment of concepts, then one must possess the power to deploy those concepts prior to experience. I argue that the plausibility of this argument rests on a subtle equivocation. It’s true that conceptualism requires a particular kind of power to deploy concepts prior to (...) experience, but not the sort referenced in the intuitive constraint mentioned above. I end by proposing how the conceptualist might satisfy this constraint. I conclude that conceptualism is better situated to account for primitive concept acquisition than typically thought. (shrink)

Many think that expressivists have a special problem with negation. I disagree. For if there is a problem with negation, I argue, it is a problem shared by those who accept some plausible claims about the nature of intentionality. Whether there is any special problem for expressivists turns, I will argue, on whether facts about what truth-conditions beliefs have can explain facts about basic inferential relations among those beliefs. And I will suggest that the answer to this last question is, (...) on most plausible attempts at solving the problem of intentionality, ‘no’. (shrink)

Mind &Language, Volume 34, Issue 5, Page 667-680, November 2019.

It is generally accepted that, in the cognitive and neural sciences, there are both computational and mechanistic explanations. We ask how computational explanations can integrate into the mechanistic hierarchy. The problem stems from the fact that implementation and mechanistic relations have different forms. The implementation relation, from the states of an abstract computational system to the physical, implementing states is a homomorphism mapping relation. The mechanistic relation, however, is that of part/whole; the explaining features in a mechanistic explanation are the (...) components of the explanandum phenomenon and their causal organization. Moreover, each component in one level of mechanism is constituted and explained by components of an underlying level of mechanism. Hence, it seems, computational variables and functions cannot be mechanistically explained by the medium-dependent states and properties that implement them. How then, do the computational and the implementational integrate to create the mechanistic hierarchy? After explicating the general problem, we further demonstrate it through a concrete example, of reinforcement learning, in the cognitive and neural sciences. We then examine two possible solutions. On one solution, the mechanistic hierarchy embeds at the same levels computational and implementational properties. This picture fits with the view that computational explanations are mechanistic sketches. On the other solution, there are two separate hierarchies, one computational and another implementational, which are related by the implementation relation. This picture fits with the view that computational explanations are functional and autonomous explanations. It is less clear how these solutions fit with the view that computational explanations are full-fledged mechanistic explanations. Finally, we argue that both pictures are consistent with the reinforcement learning example, but that scientific practice does not align with the view that computational models are merely mechanistic sketches. (shrink)

Healey et al. introduce the special issue with a brief overview of work on communication in the Cognitive Sciences and some of the historical and conceptual influences that have marginalized the study of miscommunication. Drawing on more recent work in Cognitive Science and Conversation Analysis they argue that miscommunication is in fact a highly structured, ubiquitous phenomenon that is fundamental to human interaction.

The concept of narrow content is still under discussion in the debate over mental representation. In the paper, one-factor dimensional accounts of representation are analyzed, particularly the case of Fodor's methodological solipsism. In methodological solipsism, semantic properties of content are arguably eliminated in favor of syntactic ones. If “narrow content” means content properties independent of external factors to a system (as in Segal's view), the concept of content becomes elusive. Moreover, important conceptual problems with one-factor dimensional account are pointed out (...) as a result of analysis arguments presented by J. Searle, S. Harnad and T. Burge. Furthermore, these problems are illustrated with psychological and ethological examples. Although understanding content as partially independent from contextual factors allows theorists to preserve content properties, it seems that understanding content in total abstraction from external factors of these properties is implausible. As a result, internalism is rejected in favor of externalism. (shrink)

Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats that of humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking (...) machines will have to reach beyond current engineering trends in both what they learn and how they learn it. Specifically, we argue that these machines should build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; ground learning in intuitive theories of physics and psychology to support and enrich the knowledge that is learned; and harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes toward these goals that can combine the strengths of recent neural network advances with more structured cognitive models. (shrink)