Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to (...) adaptive success. This target article critically examines this approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency. (shrink)

What are the prospects for a cognitive science of meaning? As stated, we think this question is ill posed, for it invites the conflation of several importantly different semantic concepts. In this paper, we want to distinguish the sort of meaning that is an explanandum for cognitive science—something we are going to call meaning—from the sort of meaning that is an explanans in cognitive science—something we are not going to call meaning at all, but rather content. What we are going (...) to call meaning is paradigmatically a property of linguistic expressions or acts: what one’s utterance or sentence means, and what one means by it. What we are going to call content is a property of, among other things, mental representations and indicator signals. We will argue that it is a mistake to identify meaning with content, and that, once this is appreciated, some serious problems emerge for grounding meaning in the sorts of content that cognitive science is likely to provide. (shrink)

Fodor advocates a view of cognitive processes as computations defined over the language of thought (or Mentalese). Even among those who endorse Mentalese, considerable controversy surrounds its representational format. What semantically relevant structure should scientific psychology attribute to Mentalese symbols? Researchers commonly emphasize logical structure, akin to that displayed by predicate calculus sentences. To counteract this tendency, I discuss computational models of navigation drawn from probabilistic robotics. These models involve computations defined over cognitive maps, which have geometric rather than logical (...) structure. They thereby demonstrate the possibility of rational cognitive processes in an exclusively non-logical representational medium. Furthermore, they offer much promise for the empirical study of animal navigation. (shrink)

1. Introduction 2. Reward-Guided Decision Making 3. Content in the Model 4. How to Deflate a Metarepresentational Reading Proust and Carruthers on metacognitive feelings 5. A Deflationary Treatment of RPEs? 5.1 Dispensing with prediction errors 5.2 What is use of the RPE focused on? 5.3 Alternative explanations—worldly correlates 5.4 Contrast cases 6. Conclusion Appendix: Temporal Difference Learning Algorithms.

We discuss Russell's 1913 essay arguing for the irrelevance of the idea of causation to science and its elimination from metaphysics as a precursor to contemporary philosophical naturalism. We show how Russell's application raises issues now receiving much attention in debates about the adequacy of such naturalism, in particular, problems related to the relationship between folk and scientific conceptual influences on metaphysics, and to the unification of a scientifically inspired worldview. In showing how to recover an approximation to Russell's conclusion (...) while explaining scientists' continuing appeal to causal ideas (without violating naturalism by philosophically correcting scientists) we illustrate a general naturalist strategy for handling problems around the unification of sciences that assume different levels of naïveté with respect to folk conceptual frameworks. We do this despite rejecting one of the premises of Russell's argument, a version of reductionism that was scientifically plausible in 1913 but is not so now. (shrink)

Many philosophers worry that the classical computational theory of mind (CTM) engenders epiphenomenalism. Building on Block’s (1990) discussion, I formulate a particularly troubling version of this worry. I then present a novel solution to CTM’s epiphenomenalist conundrum. I develop my solution within an interventionist theory of causal relevance. My solution departs substantially from orthodox versions of CTM. In particular, I reject the widespread picture of digital computation as formal syntactic manipulation.1.

In the last decade several prominent critics have charged that invocation of representations is not only not essential for cognitive science, but should be avoided. These claims have been followed by counterarguments demonstrating that the notion certainly is important in explanations of cognitive phenomena. Analyzing some important contributions to the debate, Anthony Chemero has argued that representationalists still need to explain the significance of the notion once there is an available formal account of a system and has, accordingly, challenged representationalists (...) to provide such an explanation. This paper's first part explains why the representationalist should take an interest in Chemero's challenge. It discusses William Bechtel 's account of the representational structure of the Watt Governor, which, among other things, was motivating Chemero to question the relevance of a representational account once a dynamical one is available. The second part contains the answer to Chemero's challenge. It is motivated by the thought that only a representational account of the Watt Governor with a comparable level of detail could possibly add explanatory value to a dynamical account. However, accepting the account also means that it becomes difficult to understand dynamical and representational accounts as rivals. Instead, it would be more adequate to speak of a dynamical account of the representational structure. (shrink)

After a decade of intense debate about mechanisms, there is still no consensus characterization. In this paper we argue for a characterization that applies widely to mechanisms across the sciences. We examine and defend our disagreements with the major current contenders for characterizations of mechanisms. Ultimately, we indicate that the major contenders can all sign up to our characterization.

This work represents an attempt to stake out the landscape for dynamicism based on a radical dismissal of the information-processing paradigm that dominates the philosophy of cognitive science. In Section 2, after setting up the basic toolkit of a theory of minimal representationalism, I introduce the central tenets of dynamic systems theory (DST) by discussing recent research in the dynamics of embodiment (Thelen et al. [2001]) in the perseverative-reaching literature. A recent proposal on the dynamics of representation--the dynamic field approach (...) (Spencer and Schöner [2003])-- according to which the alleged representational gap between DST and representational theories of cognition needs to be bridged in order to explain higher-order cognitive activity will then be reviewed. In Section 3 I shall argue that Spencer and Schöner's attempt to bridge the representational gap may jeopardize the whole (antirepresentationalist) spirit of the DST project. In order to show why, I shall introduce the key concepts of "reliability of environment" and "primagenesis", and argue that DST can account for de-coupled, offline cognitive activity with no need of positing representational resources. Conclusions and directions for future research will follow. (shrink)

Preface and Acknowledgments Introduction PART I Intentionality Chapter 1 Fodor’ Guide to Mental Representation: The Intelligent Auntie’s Vade-Mecum Chapter 2 Semantics, Wisconsin Style Chapter 3 A Theory of Content, I: The Problem Chapter 4 A Theory of Content, II: The Theory Chapter 5 Making Mind Matter More Chapter 6 Substitution Arguments and the Individuation of Beliefs Chapter 7 Stephen Schiffer’s Dark Night of The Soul: A Review of Remnants of Meaning PART II Modularity Chapter 8 Précis of The Modularity of (...) Mind Chapter 9 Why Should the Mind Be Modular? Chapter 10 Observation Reconsidered Appendix: A Reply to Churchland’s ‘Perceptual Plasticity and Theoretical Neutrality" References Index of Names. (shrink)

This paperback edition contains a preface placing the book in the context of recent work in the area.

"This is an important new Cummins work.

Tyler Burge presents an original study of the most primitive ways in which individuals represent the physical world. By reflecting on the science of perception and related psychological and biological sciences, he gives an account of constitutive conditions for perceiving the physical world, and thus aims to locate origins of representational mind.

Advocates of dynamical systems theory (DST) sometimes employ revolutionary rhetoric. In an attempt to clarify how DST models differ from others in cognitive science, I focus on two issues raised by DST: the role for representations in mental models and the conception of explanation invoked. Two features of representations are their role in standing-in for features external to the system and their format. DST advocates sometimes claim to have repudiated the need for stand-ins in DST models, but I argue that (...) they are mistaken. Nonetheless, DST does offer new ideas as to the format of representations employed in cognitive systems. With respect to explanation, I argue that some DST models are better seen as conforming to the covering-law conception of explanation than to the mechanistic conception of explanation implicit in most cognitive science research. But even here, I argue, DST models are a valuable complement to more mechanistic cognitive explanations. (shrink)

While neuroscientists often characterize brain activity as representational, many philosophers have construed these accounts as just theorists’ glosses on the mechanism. Moreover, philosophical discussions commonly focus on finished accounts of explanation, not research in progress. I adopt a different perspective, considering how characterizations of neural activity as representational contributes to the development of mechanistic accounts, guiding the investigations neuroscientists pursue as they work from an initial proposal to a more detailed understanding of a mechanism. I develop one illustrative example involving (...) research on the information-processing mechanisms mammals employ in navigating their environments. This research was galvanized by the discovery in the 1970s of place cells in the hippocampus. This discovery prompted research in what the activity of these cells represents and how place representations figure in navigation. It also led to the discovery of a host of other types of neurons—grid cells, head-direction cells, boundary cells—that carry other types of spatial information and interact with place cells in the mechanism underlying spatial navigation. As I will try to make clear, the research is explicitly devoted to identifying representations and determining how they are constructed and used in an information processing mechanism. Construals of neural activity as representations are not mere glosses but are characterizations to which neuroscientists are committed in the development of their explanatory accounts. (shrink)

What is life? For four centuries, it has been believed that the only possible scientific approach to this question proceeds from the Cartesian metaphor -- organism as machine. Therefore, organisms are to be studied and characterized the same way "machines" are; the same way any inorganic system is. Robert Rosen argues that such a view is neither necessary nor sufficient to answer the question. He asserts that life is not a specialization of mechanism, but rather a sweeping generalization of it. (...) Above all, Rosen argues that renouncing mechanism does not mean abandoning science. A radical alternative is proposed, drawn equally from experience in biology, physics, and mathematics; an alternative which draws attention to a new class of complex systems, which are radically different from mechanism. (shrink)

In this book, Daniel Hutto and Erik Myin promote the cause of a radically enactive, embodied approach to cognition that holds that some kinds of minds -- basic minds -- are neither best explained by processes involving the manipulation of ...

While philosophers of mind have been arguing over the status of mental representations in cognitive science, cognitive scientists have been quietly engaged in studying perception, action, and cognition without explaining them in terms of mental representation. In this book, Anthony Chemero describes this nonrepresentational approach, puts it in historical and conceptual context, and applies it to traditional problems in the philosophy of mind. Radical embodied cognitive science is a direct descendant of the American naturalist psychology of William James and John (...) Dewey, and follows them in viewing perception and cognition to be understandable only in terms of action in the environment. Chemero argues that cognition should be described in terms of agent-environment dynamics rather than in terms of computation and representation. After outlining this orientation to cognition, Chemero proposes a methodology: dynamical systems theory, which would explain things dynamically and without reference to representation. He also advances a background theory: Gibsonian ecological psychology, "shored up" and clarified. Chemero then looks at some traditional philosophical problems through the lens of radical embodied cognitive science and concludes that the comparative ease with which it resolves these problems, combined with its empirical promise, makes this approach to cognitive science a rewarding one. "Jerry Fodor is my favorite philosopher," Chemero writes in his preface, adding, "I think that Jerry Fodor is wrong about nearly everything." With this book, Chemero explains nonrepresentational, dynamical, ecological cognitive science as clearly and as rigorously as Jerry Fodor explained computational cognitive science in his classic work The Language of Thought. (shrink)

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind is (...) that the mechanism explains the rich, deep, and multifaceted character of our conscious perception. It also gives a unified account of how perception is sculpted by attention, and how it depends on action. The mind is revealed as having a fragile and indirect relation to the world. Though we are deeply in tune with the world we are also strangely distanced from it. (shrink)

In the book, I argue that the mind can be explained computationally because it is itself computational—whether it engages in mental arithmetic, parses natural language, or processes the auditory signals that allow us to experience music. All these capacities arise from complex information-processing operations of the mind. By analyzing the state of the art in cognitive science, I develop an account of computational explanation used to explain the capacities in question.

Cognitive representation is the single most important explanatory notion in the sciences of the mind and has served as the cornerstone for the so-called 'cognitive revolution'. This book critically examines the ways in which philosophers and cognitive scientists appeal to representations in their theories, and argues that there is considerable confusion about the nature of representational states. This has led to an excessive over-application of the notion - especially in many of the fresher theories in computational neuroscience. Representation Reconsidered shows (...) how psychological research is actually moving in a non-representational direction, revealing a radical, though largely unnoticed, shift in our basic understanding of how the mind works. (shrink)

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 The Psychological Reality (...) of Programs: Strong Equivalence 5 Constraining Functional Architecture 6 The Bridge from Physical to Symbolic: Transduction 7 Functional Architecture and Analogue Processes 8 Mental Imagery and Functional Architecture 9 Epilogue: What is Cognitive Science the Science of? (shrink)

This article focuses on the problem of representational content. Accounting for representational content is the central issue in contemporary naturalism: it is the major remaining task facing a naturalistic conception of the world. Representational content is also the central barrier to contemporary cognitive science and artificial intelligence: it is not possible to understand representation in animals nor to construct machines with genuine representation given current (lack of) understanding of what representation is. An elaborated critique is offered to current approaches to (...) representation, arguing that the basic underlying approach is, at root, logically incoherent, and, thus, that standard approaches are doomed to failure. An alternative model of representation - interactivism - is presented that avoids or solves the problems facing standard approaches. Interactivism is framed by a version of functionalism, and a naturalization of that functionalism completes an outline of a naturalization of representation and representational content. (shrink)

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control their own conditions so as to increase their functionality (they self-regulate). Living systems self-regulate in order to increase their own viability. These increasingly stronger conditions, anticipation, autonomy and viability, can give an insight into progressively stronger classes of models of autonomy. I will argue that stronger forms are the relevant ones for Artificial Life. This (...) has consequences for the design of and accurate simulation of living systems. Keywords: autonomy, modelling, function, simulation, anticipation, emergence DUBOIS’ CONJECTURE Autonomy basically means self-regulation. Self-regulation implies internal control of system states to achieve greater functionality, either internally or interactively with the environment. Functionality, as a teleological notion, implies that the system must be directed by likely future states; that is, it must anticipate and (possibly) adapt to likely future states. Functionality does not require autonomy (assuming functional goals are externally set), but merely that current states of the system can select suitable future states on the basis of suitable input. In this.. (shrink)