One of the most influential methodological contributions of twentieth‐century philosophy was the approach known as conceptual analysis. The majority of experimental philosophy papers are doing cognitive science. They are revealing surprising new effects and then offering explanations those effects in terms of certain underlying cognitive processes. The best way to get a sense for actual research programs in experimental philosophy is to look in detail at one particular example. This chapter considers the effect of moral (...) considerations on intuitions about intentional action, as an example. Working in conceptual analysis aimed to develop analyses of concepts, and in that context, the obvious proposal would be that people should be aiming for simple analyses of concepts. The chapter also focuses on the study of intuitions about knowledge. Experimental philosophy has sought to capture the patterns in people's intuitions through theories about underlying cognitive processes. (shrink)

Reference to Cartesianism is a permanent feature of the contemporary works in the fields of philosophy of mind and cognitive science. Its function is not so much to provide a historical exegesis of Descartes as to highlight some supposed aspects of the Cartesian theory of mind, more precisely those that are still reported to inform the current philosophical and scientific research and that remain to be improved on. Thus not only is the adjective Cartesian used to refer directly (...) to Descartes, but also to designate modern approaches to the mind which, though breaking with Cartesianism on several points, are nevertheless thought to inherit important Cartesian errors. Moreover, in line with this one may note that the term Cartesian is essentially employed in a critical sense. And indeed, for most contemporary theorists, Cartesianism is regarded as the arch-enemy. In the present contribution we intend to draw a portrait of this enemy from the way the notion of Cartesianism is sometimes used in the philosophy of mind and in cognitive science. Our analysis, which is not meant to be exhaustive, aims at accounting for reference to the Cartesian figure and the issues it raises in the above-mentioned fields. (shrink)

Evolutionary science (ES) and contextual behavioral science (CBS) have developed largely independently during the last half century. However, the earlier histories of these two bodies of knowledge are thoroughly entwined. ES provides a unifying theoretical framework for the biological sciences, and is increasingly being applied to human-related sciences. Meanwhile, CBS is concerned with influencing human behavior in a practical sense. This groundbreaking volume seeks to integrate ES and CBS to promote real, positive change in peoples' lives. Evolution (...) and Contextual Behavioral Science offers a unique glimpse into the histories of ES and CBS, shows how they are intrinsically linked, and outlines why their integration--or, reunification--is essential. By examining these two schools of thought side by side, you'll gain an understanding of why functional and contextual approaches in CBS need to be combined with ES for both fields to advance more rapidly. Finally, rather than the sequential relationship that is typically imagined between ES and CBS, you'll discover how an integrated relationship between these two sciences will result in a better framework for understanding predicting, and influencing human behavior--back cover. (shrink)

_Abstract_: The question posed in the title serves as a springboard to examine the interdisciplinary nature of cognitive science and the role philosophy should play. I will argue that philosophy has a clearly defined role to play over and above the contributions made by philosophies specific to the various disciplines engaged in cognitive science. I also point out that by engaging with cognitive science – an endeavor defined by a clear scientific goal – philosophy (...) itself will have to change in ways that are bound to affect the future of philosophizing. In the first part of this paper, I play devil’s advocate, arguing that philosophy should not be amongst the disciplines engaged in cognitive science. In the second part, I discuss how the relationship between philosophy and psychology has been changed by their common participation in cognitive science: psychology is now admittedly philosophical and philosophy has become naturalized. In the third part, I suggest that philosophy is better equipped than psychology to handle the thorny question of representation in cognitive science. In the fourth part and conclusion, I argue that cognitive science will influence both the theory and practice of philosophy: the futures of cognitive science and philosophy are tied together. _Keywords_: Philosophy; Cognitive Science; Cognitive Psychology; Naturalism; Epistemology _Quale filosofia – se una ce ne vuole – per la scienza cognitiva?_ _Riassunto_: L’interrogativo posto nel titolo funge da punto di partenza per analizzare la natura interdisciplinare della scienza cognitiva e il ruolo che la filosofia dovrebbe avere al suo interno. Sosterrò che alla filosofia spetti un ruolo ben definito, al di là dei contributi forniti dai particolari indirizzi filosofici coinvolti nella scienza cognitiva. Sottolineerò anche che, confrontandosi con la scienza cognitiva – un ambito caratterizzato da un chiaro obiettivo scientifico – la filosofia stessa dovrà cambiare, assumendo modalità che influenzeranno il futuro del filosofare. Nella prima parte di questo articolo metterò le vesti dell’avvocato del diavolo, sostenendo come la filosofia non dovrebbe essere tra le discipline coinvolte nella scienza cognitiva. Nella seconda parte discuterò come il rapporto tra filosofia e psicologia sia mutato per effetto della comune partecipazione al progetto della scienza cognitiva: ora la psicologia è apertamente filosofica e la filosofia è filosofia naturalizzata. Nella terza parte mostrerò come la filosofia sia meglio equipaggiata della psicologia per fronteggiare l’ostico problema della rappresentazione nella scienza cognitiva. Nella quarta parte e nelle conclusioni sosterrò che la scienza cognitiva potrà influenzare la teoria e la pratica del filosofare: il futuro della scienza cognitiva e della filosofia sono reciprocamente legati. _Parole chiave_: Filosofia; Scienza cognitiva; Psicologia cognitiva; Naturalismo; Epistemologia. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Mild Cognitive Impairment:Which Kind Is It?Andy Hamilton (bio)Keywordshuman kinds, mild cognitive impairment, multiple personality disorder, practical kinds, social constructionThere is much stimulating material in the Graham and Ritchie's paper (2006), concerning not just disease-classification but also the ethics of diagnosis. My concern is with the way in which they adduce Ian Hacking's views in the philosophy of science in support of their own. The authors quote (...) with approval his "dynamic nominalism" and its influence on Zachar's concept of "practical kinds." Hacking's view, as the authors quote it, is that "People classified in a certain way tend to conform to or grow into the ways that they are described; but they also evolve in their own ways, so that the classifications and descriptions have to be constantly revised" (1995, 21). The act of classifying changes both the classifier and the subject of classification, resulting in facts and categories that are both socially created and real. Hacking calls this "the looping effect of human kinds," and comments that "Multiple personality [disorder] is an almost too perfect illustration of this feedback effect" (1995, 21). The authors comment that Zachar (2000) builds on Hacking's position, discarding essentialist notions of classification that are limited to inherent biological properties, and turning instead to "practical kinds—nonarbitrary cultural artifacts intended to meet pragmatic needs (e.g. therapeutic, predictive prognostic, labeling effects, and physiology)" (Graham and Ritchie 2006, 36). Practical kinds, they believe, offer a way out of the clinical approach focused on mild cognitive impairment (MCI) as a precursor to, or mild form of, Alzheimer's disease. The inclination of the authors, as I read them, is to treat MCI as a practical or human kind, and not, like Alzheimer's disease, as a natural kind.My concern is whether the "looping effect of human kinds" can be transferred to the case of MCI from Hacking's original case study in Rewriting the Soul, multiple personality disorder (MPD). Hacking wished there to undermine the traditional debate over whether MPD is a "social or psychiatric artifact." He claims, correctly I think, that the presupposition behind the question "Is MPD a real disorder as opposed to a product of social circumstances?" should be rejected. The fact that a disorder is a product of social circumstances does not make it less real (1995, 12). On the looping of human kinds, Hacking comments that "The concept of child abuse [implicated in MPD] may itself be so made and molded by attempts at knowledge and intervention, and social reaction to these studies, that there is no stable object, child abuse, to have knowledge about." This is a "no fact of the matter" response, and it [End Page 51] is based on the recognition of conceptual change. He later adds that child abuse "is a real evil, and it was so before the concept was constructed. It was nevertheless constructed. Neither reality nor construction should be in question" (1995, 61, 68). However, Hacking's conclusions about the reality of MPD express only a muted skepticism. Utilitarian skeptics approach this question by asking, "What is the most effective treatment?" Hacking writes that "in their hearts [such skeptics] suspect that the outcome of multiple therapy [therapy that condones or even encourages the development of multiples in the patient] is a type of false consciousness" (1995, 267). The skeptics about MPD are making a moral judgment, he believes; but on whether that moral judgment is correct, he is silent, although the suspicion must be that he agrees with it.How do these considerations apply to the case of MCI? Graham and Ritchie rightly note that classifying a subject as suffering from MCI, and informing them of the diagnosis, will affect them adversely—it will cause suffering not least because there is at present no cure. However, it must surely be conceded that any disease at all—physical or mental—is a social entity insofar as it involves behavioral ascriptions to the subject concerning their incapacity. The authors also note the vested interests—especially from the pharmaceutical industry—in developing a diagnostic category of MCI. These interests are present in the development of any significant diagnostic... (shrink)

About 30 years ago, the Dynamical Hypothesis instigated a variety of insights and transformations in cognitive science. One of them was the simple observation that, quite unlike trial-based tasks in a laboratory, natural ecologically valid behaviors almost never have context-free starting points. Instead, they produce lengthy time series data that can be recorded with dense-sampling measures, such as heartrate, eye movements, EEG, etc. That emphasis on studying the temporal dynamics of extended behaviors may have been the trigger that led (...) to a rethinking of what a “representation” is, and then of what a “cognitive agent” is. This most recent and perhaps most revolutionary transformation is the idea that a cognitive agent need not be a singular physiological organism. Perhaps a group of organisms, such as several people working on a joint task, can temporarily function as one cognitive agent – at least while they're working adaptively and successfully. (shrink)

Philosophy is a cognitive enterprise. In multiple senses, it is continuous with other sciences (including natural sciences, social sciences, and Humanities). (1) As far as its subject matter is concerned, like other sciences, philosophy is also a part of the overall efforts of human beings to understand the world in which we live. (2) In terms of their methodologies, there is no substantive difference between philosophy, common sense, and science. Just as scientific (...) methodology is the refinement of common-sense methodology, philosophical methodology is also the refinement and summary of common sense and scientific methodologies. (3) In terms of their utilities, philosophy and science are both designed to help people live better in the world, and to lead a decent and dignified life, especially a meaningful and valuable life. (4) It is the correct attitude and practice of dealing with the relationship between philosophy and the history of philosophy to study and enter philosophy through the history of philosophy, to critically reflect on the previous philosophical theories, to open up new fields, to use new methods, and to put forward new theories to develop philosophy. (5) The following two assertions about philosophy and science are just taken for granted, and specious: science relies on observation and experiment, and philosophy resorts to interpretation and understanding, while science focuses on "what is" and philosophy focuses on "what it should be". (shrink)

Until very recently it could have been said that most approaches to the philosophy of science were “cognitive.” This includes logical positivism (see logical positivism), as well as later, historically based philosophies of science, such as that of Imre Lakatos (see lakatos). Here the contrast is between the cognitive and the psychological or social dimensions of science. Central to all such “cognitive” approaches is a robust notion of rationality, or rational progress, in the evaluation of scientific (...) theories or research programmes (see theories). Carnap sought an inductive logic that would make the evaluation of hypotheses rational in the way that deductive inference is rational. Lakatos defined rational progress in terms of increasing empirical content. For both it was essential that the philosophy of science exhibit science as a rational, rather than a merely psychological or social, enterprise. (shrink)

Cross-cultural research provides invaluable information about the origins of and explanations for cognitive and behavioral diversity. Interest in cross-cultural research is growing, but the field continues to be dominated by WEIRD (Western, Educated, Industrialized, Rich, and Democratic) researchers conducting WEIRD science with WEIRD participants, using WEIRD protocols. To make progress toward improving cognitive and behavioral science, we argue that the field needs (1) data workflows and infrastructures to support long-term high-quality research that is compliant with open-science (...) frameworks; (2) process and participation standards to ensure research is valid, equitable, participatory, and inclusive; (3) training opportunities and resources to ensure the highest standards of proficiency, ethics, and transparency in data collection and processing. Here we discuss infrastructures for cross-cultural research in cognitive and behavioral sciences which we call __Cross-Cultural Data Infrastructures (CCDIs).__ We recommend building global networks of psychologists, anthropologists, demographers, experimental philosophers, educators, and cognitive, learning, and data scientists to distill their procedural and methodological knowledge into a set of community standards. We identify key challenges including protocol validity, researcher diversity, community inclusion, and lack of detail in reporting quality assurance and quality control (QAQC) workflows. Our objective is to help promote dialogue and efforts towards consolidating robust solutions by working with a broad research community to improve the efficiency and quality of cross-cultural research. (shrink)

Although philosophy has been only a minor contributor to cognitive science to date, this paper describes two projects in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years and that can make theoretical and methodological contributions to cognitive science. First, stances on the mind–body problem (identity theory, functionalism, and heuristic identity theory) are relevant to cognitive science as it negotiates its relation to neuroscience (...) and cognitive neuroscience. Second, analyses of mental representations address both their vehicles and their contents; new approaches to characterizing how representations have content are particularly relevant to understanding the relation of cognitive agents to their environments. Third, the recently formulated accounts of mechanistic explanation in philosophy of science both provide perspective on the explanatory project of cognitive science and may offer normative guidance to cognitive science (e.g., by providing perspective on how multiple disciplinary perspectives can be integrated in understanding a given mechanism). (shrink)

Applying the concepts of dynamical systems theory to explain cognitive phenomena is still a fairly recent trend in cognitive science and its potential and consequences are not nearly mapped out. A decade ago, dynamical approaches were introduced as a paradigm shift in cognitive science and in this paper I concentrate on how to substantiate this claim. After having considered and rejected the possibility that continuous time is the crucial factor, I present Kelso’s model of a near-cognitive (...) phenomenon which invokes self-organization as the guiding principle. Then, the explanatory strategy implicit in this approach is explicated and its underlying assumption presented. Finally, I discuss how we should characterize this explanatory framework using the notion of emergence. (shrink)

This is the first major textbook to offer a truly comprehensive review of cognitive science in its fullest sense. Ranging across artificial intelligence models and cognitive psychology through to recent discursive and cultural theories Rom Harre offers a breathtakingly original yet accessible integration of the field. At its core this textbook addresses the question "is psychology a science?" with a clear account of scientific method and explanation and their bearing on psychological research. A pivotal figure in psychology and (...) philosophy for many decades Rom Harre has turned his unmatched breadth of reference and insight for students at all levels. Whether describing, language, categorization, memory, the brain or connectionism the book always links our intuitions about beliefs, desires and their social context to the latest accounts of their place in computational and biological models. Fluently written and well structured, this an ideal text for students. The book is divided into four basic modules, with three lectures in each; the reader is guided with helpful learning points, study and essay questions and key readings for each chapter. (shrink)

ABSTRACT:Bioethicists today are taking a greater role in the design and implementation of emerging technologies by "embedding" within the development teams and providing their direct guidance and recommendations. Ideally, these collaborations allow ethical considerations to be addressed in an active, iterative, and ongoing process through regular exchanges between ethicists and members of the technological development team. This article discusses a challenge to this embedded ethics approach—namely, that bioethical guidance, even if embraced by the development team in theory, is not easily (...) actionable in situ. Many of the ethical problems at issue in emerging technologies are associated with preexisting structural, socioeconomic, and political factors, making compliance with ethical recommendations sometimes less a matter of choice and more a matter of feasibility. Moreover, incentive structures within these systemic factors maintain them against reform efforts. The authors recommend that embedded bioethicists utilize principles from behavioral science (such as behavioral economics) to better understand and account for these incentive structures so as to encourage the ethically responsible uptake of technological innovations. (shrink)

This excellent outline of evolutionary hypotheses is compromised by severe reductionism. Other writings succeed in granting theism ontological significance without compromising rigor. The discussion of counterintuitiveness neglects coherence in memory. Bearing in mind our severely limited working memory capacity, susceptibility to religious mythologies may comprise an adaptive heuristic approach to summarizing the contingencies of the most far-reaching of life's problems.

The so-called ‘cognitive revolution’ (Gardner, 1985) in American psychology owed much to developments in adjacent disciplines, especially theoretical linguistics and computer science. Indeed, the cognitive revolution brought forth, not only a change in the conception of psychology, but also an inter-disciplinary approach to understanding the mind, involving philosophy, anthropology and neuroscience along with computer science, linguistics and psychology. Many commentators agree in dating the conception of this inter-disciplinary approach, cognitive science, to 11 September 1956, the second (...) day of a symposium on information theory held at MIT (Miller, 2003). Over the next twenty years or so, cognitive science developed an institutional presence through research centres, conferences, journals, and a substantial infusion of funds from the Alfred P. Sloan Foundation. (shrink)

ABSTRACT Since the 1970s there has been a significant paradigm shift in psychology away from behaviourism and towards cognitive psychology. Indeed a recent survey discovered that by 1983 more than half American psychologists were describing their approaches as cognitive. However, while behaviourism has had an identifiable philosophical ‘line’ in positivism, reductionism and the hypothetico‐deductive model, such a framework has been noticeably lacking from cognitive psychology. A view of cognitive psychology based on functionalism and ideas from systems (...) analysis is put forward. (shrink)

This paper is about - cognitive science's claim to obtain an empirically theory of human intelligence by experiments with intelligent machines; - the question, whether simulation yields/is explanation , i.e. whether the theory explaining the behaviour of a thing A, appropriately abstracted, as well explains the behaviour of a thing B, different in type from A, when A's and B's behaviours are indistinguishable; - the question, whether the Aristotelian ontic distinction between the natural and the artificial was in fact (...) extinguished by Descartes' materialistic intensional ontology; this question is denied by evidence of the existence of different theories of artificial and natural magnetism in current physics; - and about the comparison of the current theories of magnetism, of artificial or electromagnetism and of natural or ferromagnetism with the result that there is no uniform theory explaining all kinds of magnetism to be gained out of Maxwell's theory. Thus by counterexample is demonstrated that cognitive science's claim to obtain a theory of natural intelligence by the S:E-strategy is to be refused. Descartes' premise of the ontic indifference of the size of physical magnitudes is introduced as basis of the S:E-claim and its refutation as cause of the partial continuation of the ontic distinction between natural and artificial things in physics. (shrink)

According to a brief and very general definition Cognitive Science is an interdisciplinary scientific study of how information is represented and transformed in a human nervous system. “Information”, “representation” and “transformation” are keywords here. Many disciplines bring considerable contribution to Cognitive Science. Logic is one of them. Logic investigates these rules which allow us to recognize valid reasonings and distinguish them from those that fail to fulfill the condition of valid- ity. Thus logic investigates some representation (or representations) (...) of reasoning. Significant part of information transformed in nervous system is related to reasoning and inference. This fact opens special perspectives on applying Logic in Cognitive Science both in representing as well as in transforming information. Any formal logical system constitutes a kind of representation of a class of propositions considered as sentence content. In this way each logical system provides a representation of a broad class of belief states. At the same time any inference relation, related to a given logical system, represents a transformation of some type of information. As a consequence it would be hard to find logical investigations which could not be applied in Cognitive Science. Such an idea guided us while we were preparing the present volume. (shrink)

The main aim of the paper is to defend (the possibility of) reductionism in the neuroscience--cognitive science case. This is done in three steps. First an ontological and methodological picture is presented which acknowledges the level structure of reality but claims that because every higher level is evolutionarily preceded by the lower level(s), reductionism is as viable strategy as anything else. Secondly, a direct challenge to the two popular doctrines, namely emergentism and supervenience, is presented, the point being that (...) we don't have clear conception of what "emerging" is or how specifically to explain what something's "depending on" something or "determining" something is (in the case of supervenience). In the third part the so-called modified structuralist framework (from the structuralist philosophy of science) is proposed as an alternative model to the old Nagelian one, a model which can serve reductionistic purposes well because it admits many kinds of reduction, from approximate to very strict ones. (shrink)

How can we use what cognitive science has taught us about perception to improve the critical thinking skills of our students? What, for instance, does it tell us about subjects who think they’ve seen Bigfoot, ghosts, and other “weird things”? I explore two approaches for giving students some empirically based tools for examining cases like these. The first, which I call the “we see what we want to see” approach, focuses the idea that beliefs and desires can shape our (...) visual experiences. This approach, however, encourages students to view subjects who report weird experiences as being cognitively irresponsible and worthy of derision. The second approach, which I call the “we see what our evolutionary ancestors needed to see” approach, asserts these experiences are the result of evolutionarily designed perceptual mechanisms that specialize in representing human-like qualities. Fortunately, the second approach does not create the same problematic attitude in students as the first. (shrink)

Part I: The Life of Cognitive Science:. William Bechtel, Adele Abrahamsen, and George Graham. Part II: Areas of Study in Cognitive Science:. 1. Analogy: Dedre Gentner. 2. Animal Cognition: Herbert L. Roitblat. 3. Attention: A.H.C. Van Der Heijden. 4. Brain Mapping: Jennifer Mundale. 5. Cognitive Anthropology: Charles W. Nuckolls. 6. Cognitive and Linguistic Development: Adele Abrahamsen. 7. Conceptual Change: Nancy J. Nersessian. 8. Conceptual Organization: Douglas Medin and Sandra R. Waxman. 9. Consciousness: Owen Flanagan. 10. Decision (...) Making: J. Frank Yates and Paul A. Estin. 11. Emotions: Paul E. Griffiths. 12. Imagery and Spatial Representation: Rita E. Anderson. 13. Language Evolution and Neuromechanisms: Terrence W. Deacon. 14. Language Processing: Kathryn Bock and Susan M. Garnsey. 15. Linguistics Theory: D. Terence Langendoen. 16. Machine Learning: Paul Thagard. 17. Memory: Henry L. Roediger III and Lyn M. Goff. 18. Perception: Cees Van Leeuwen. 19. Perception: Color: Austen Clark. 20. Problem Solving: Kevin Dunbar. 21. Reasoning: Lance J. Rips. 22. Social Cognition: Alan J. Lambert and Alison L. Chasteen. 23. Unconscious Intelligence: Rhianon Allen and Arthur S. Reber. 24. Understanding Texts: Art Graesser and Pam Tipping. 25. Word Meaning: Barbara C. Malt. Part III: Methodologies of Cognitive Science:. 26. Artificial Intelligence: Ron Sun. 27. Behavioral Experimentation: Alexander Pollatsek and Keith Rayner. 28. Cognitive Ethology: Marc Bekoff. 29. Deficits and Pathologies: Christopher D. Frith. 30. Ethnomethodology: Barry Saferstein. 31. Functional Analysis: Brian Macwhinney. 32. Neuroimaging: Randy L. Buckner and Steven E. Petersen. 33. Protocal Analysis: K. Anders Ericsson. 34. Single Neuron Electrophysiology: B. E. Stein, M.T. Wallace, and T.R. Stanford. 35. Structural Analysis: Robert Frank. Part IV: Stances in Cognitive Science:. 36. Case-based Reasoning: David B. Leake. 37. Cognitive Linguistics: Michael Tomasello. 38. Connectionism, Artificial Life, and Dynamical Systems: Jeffrey L. Elman. 39. Embodied, Situated, and Distributed Cognition: Andy Clark. 40. Mediated Action: James V. Wertsch. 41. Neurobiological Modeling: P. Read Montague and Peter Dayan. 42. Production Systems: Christian D. Schunn and David Klahr. Part V: Controversies in Cognitive Science:. 43. The Binding Problem: Valerie Gray Hardcastle. 44. Heuristics and Satisficing: Robert C. Richardson. 45. Innate Knowledge: Barbara Landau. 46. Innateness and Emergentism: Elizabeth Bates, Jeffrey L. Elman, Mark H. Johnson, Annette Karmiloff-Smith, Domenico Parisi, and Kim Plunkett. 47. Intentionality: Gilbert Harman. 48. Levels of Explanation and Cognition Architectures: Robert N. McCauley. 49. Modularity: Irene Appelbaum. 50. Representation and Computation: Robert S. Stufflebeam. 51. Representations: Dorrit Billman. 52. Rules: Terence Horgan and John Tienson. 53. Stage Theories Refuted: Donald G. Mackay. Part VI: Cognitive Science in the Real World:. 54. Education: John T. Bruer. 55. Ethics: Mark L. Johnson. 56. Everyday Life Environments: Alex Kirlik. 57. Institutions and Economics: Douglass C. North. 58. Legal Reasoning: Edwina L. Rissland. 59. Mental Retardation: Norman W. Bray, Kevin D. Reilly, Lisa F. Huffman, Lisa A. Grupe, Mark F. Villa, Kathryn L. Fletcher, and Vivek Anumolu. 60. Science: William F. Brewer and Punyashloke Mishra. Selective Biographies of Major Contributors to Cognitive Science: William Bechtel and Tadeusz Zawidzki. (shrink)

This chapter contains sections titled: Introduction Historical Background: Behaviorism and the Cognitive Revolution Current Topics Future Directions.

This volume introduces central issues in cognitive science by means of debates on key questions. The debates are written by renowned experts in the field. The debates cover the middle ground as well as the extremes Addresses topics such as the amount of innate knowledge, bounded rationality and the role of perception in action. Provides valuable overview of the field in a clear and easily comprehensible form.

Hume is an experimental philosopher who attempts to understand why we think, feel, and act as we do. But how should we evaluate the adequacy of his proposals? This chapter examines Hume’s account from the perspective of interdisciplinary work in cognitive science.

Economic value additions to knowledge and demand provide practical, embedded and extensible meaning to philosophizing cognitive systems. Evaluation of a cognitive system is an empirical matter. Thinking of science in terms of distributed cognition (interactionism) enlarges the domain of cognition. Anything that actually contributes to the specific quality of output of a cognitive system is part of the system in time and/or space. Cognitive science studies behaviour and knowledge structures of experts and categorized structures based on (...) underlying structures. Knowledge representation through understanding of ‘epistemic cultures’ is an evolutionary stage. But cognition goes beyond knowledge representation. Notwithstanding the importance of epistemology of phenomena, the practicability cum philosophical aspects of machine learning needs to be seen in dynamic behaviour in socio-economic-technical value additions if human machine interaction processes that are context specific are incorporated into strong artificial intelligent systems. Cognitive Science is also studied from both computational and biological angles. Evolution of interactive forms of reasoning through understanding of meta-language of computations or biological learning processes is possible. But the limitation of historical cultures predefines the role of interactive processes in user-networks beyond technology networks. Despite this limitation, inclusive development notions of a heterogeneous national society such as India or Europe can be tested and incorporated. (shrink)

Over the past 10 years, Cognitive Linguistics has taken a quantitative turn. Yet, concerns have been raised that this preoccupation with quantification and modelling may not bring us any closer to understanding how language works. We show that this objection is unfounded, especially if we rely on modelling techniques based on biologically and psychologically plausible learning algorithms. These make it possible to take a quantitative approach, while generating and testing specific hypotheses that will advance our understanding of how knowledge (...) of language emerges from exposure to usage. (shrink)

Mechanistic frameworks of investigation and explanation dominate the cognitive, neural, and psychological sciences. In this dissertation, I argue that mechanistic frameworks cannot, in principle, explain some kinds of cognition. In its place, I argue that complexity science has methods and theories more appropriate for investigating and explaining some cognitive phenomena. -/- I begin with an examination of the term 'cognition.' I defend the idea that "cognition" has been a moving target of investigation in the relevant sciences. (...) As such it is not historically true that there has been a thoroughly entrenched and agreed upon conception of "cognition." Next, I take up mechanistic frameworks. Although 'mechanism' is an umbrella term for a set of loosely related characteristics, there are common features: linearity, localization, and component dominance. I then describe complexity science, with emphasis on its utilization of dynamical systems modeling. Next, I discuss two phenomena that typically fall under the purview of complexity science: nonlinearity and interaction dominance. -/- A complexity science framework guided by the theory of self-organized criticality and utilizing the methods of dynamical systems modeling can surmount a number of challenges that face mechanistic frameworks when investigating some kinds of cognition. The first challenge is epistemic and concerns the inadequacy of mechanistic frameworks to facilitate the comprehensibility of massive amounts of data across various scales and areas of inquiry. I argue that complexity science is more appropriate for making big data comprehensible when investigating cognition, particularly across disciplines. I demonstrate this via an approach called nested dynamical modeling (NDM). NDM can facilitate comprehensibility of large amounts of data obtained from various scales of investigation by eliminating irrelevant degrees of freedom of that system as relates to the target of investigation. -/- The second shortcoming concerns ontological blind spots within mechanistic frameworks. Cognitive phenomena like extended cognition often fail to meet most, if not all, of the criteria assumed by many mechanistic approaches, especially component dominance. I argue that research guided by the notion of interaction dominance allows for extended cognition to be a real, empirically supported phenomenon within complex systems frameworks. In this chapter I discuss some of my experimental work on extended cognitive systems. -/- The search for mechanisms can be a reasonable starting position when attempting to explain natural phenomena in the life sciences. However, too strict of an adherence to theoretical and methodological commitments such as linearity, localization, and component dominance can result in intractable epistemic challenges and ontological blind spots. Complexity science has theories and methods to overcome such challenges in the investigation of cognition. (shrink)

Normative questions – particularly questions about what we should believe and how we should behave – have always been high on the agenda for philosophers, and over the centuries there has been no shortage of answers proposed. But this abundance of answers raises yet another fundamental philosophical question: How should we evaluate the proposed answers; how can we determine whether an answer to a normative question is a good one? The best known and most widely used method for evaluating answers (...) to normative questions can be traced all the way back to Plato. Recently, however, cognitive scientists interested in cross cultural differences have reported findings that pose a serious challenge to this venerable philosophical method. Indeed, in light of these new findings some philosophers – I am one of them – have come to think that after 2400 years it may be time for philosophy to stop relying on Plato’s method. In the pages that follow I’ll sketch the path that led me to this conclusion. (shrink)

Duhem’s problem arises especially in scientific contexts where the tools and procedures of measurement and analysis are numerous and complex. Several philosophers of cognitive science have cited its manifestations in fMRI as grounds for skepticism regarding the epistemic value of neuroimaging. To address these Duhemian arguments for skepticism, I offer an alternative approach based on Deborah Mayo’s error-statistical account in which Duhem's problem is more fruitfully approached in terms of error probabilities. This is illustrated in examples such as the (...) use of probabilistic brain atlases, comparison of different preprocessing protocols with respect to their error characteristics, and statistical modeling of fMRI data. These examples demonstrate the ways in which we can better understand and formulate the general methodological problem and direct the way toward alternative approaches to neuroimaging in philosophy of cognitive science, in which we can be more balanced and productive in our scrutiny of the epistemic value of neuroimaging studies. (shrink)

Cognitive Science is a single-source undergraduate text that broadly surveys the theories and empirical results of cognitive science within a consistent computational perspective. In addition to covering the individual contributions of psychology, philosophy, linguistics, and artificial intelligence to cognitive science, the book has been revised to introduce the connectionist approach as well as the classical symbolic approach and adds a new chapter on cognitively related advances in neuroscience. Cognitive science is a rapidly evolving field that (...) is characterized by considerable contention among different views and approaches. Cognitive Science presents these in a relatively neutral manner. It covers many new orientations theories and findings, embedding them in an integrated computational perspective and establishing a sense of continuity and contrast with more traditional work in cognitive science. The text assumes no prerequisite knowledge, introducing all topics in a uniform, accessible style. Many topics, such as natural language processing and vision, however, are developed in considerable depth, which allows the book to be used with more advanced undergraduates or even in beginning graduate settings. A Bradford Book. (shrink)

A popular argument form uses general theories of cognitive architecture to motivate conclusions about the nature of moral cognition. This paper highlights the possibility for modus tollens reversal of this argument form. If theories of cognitive architecture generate predictions for moral cognition, then tests of moral thinking provide feedback to cognitive science. In certain circumstances, philosophers' introspective attention to their own moral deliberations can provide unique data for these tests. Recognizing the possibility for this sort of feedback (...) helps to illuminate a deep continuity between the disciplines. (shrink)

A concern for cultural specificity, the staple of traditional anthropological research, survives the transition to domain-specific accounts of cognitive structuring such as Atran's, and is arguably better off for having made the transition. The identification of domain-specific processes provide us with criteria for sorting cultural differences and integrating cultural concerns within cognitive science.

Introduction. During the past two decades philosophers of psychology have considered a large variety of computational models for philosophy of mind and more recently for cognitive science. Among the suggested models are computer programs, Turing machines, pushdown automata, linear bounded automata, finite state automata and sequential machines. Many philosophers have found finite state automata models to be the most appealing, for various reasons, although there has been no shortage of defenders of programs and Turing machines. A paper by (...) Arthur Burks convinced me long ago that “all natural human functions” are, or can be fruitfully modeled to be, finite state automata with output. Further work in the field has reinforced this conviction. There is room, however, for the use of any of the above models in philosophy of mind and in the ongoing development of cognitive science. (shrink)

Some researchers and autistic activists have recently suggested that because some ‘autism-related’ behavioural atypicalities have a function or purpose they may be desirable rather than undesirable. Examples of such behavioural atypicalities include hand-flapping, repeatedly ordering objects (e.g., toys) in rows, and profoundly restricted routines. A common view, as represented in the Diagnostic and Statistical Manual of Mental Disorders (DSM) IV-TR (APA, 2000), is that many of these behaviours lack adaptive function or purpose, interfere with learning, and constitute the non-social behavioural (...) dysfunctions of those disorders making up the Autism Spectrum. As the DSM IV-TR continues to be the reference source of choice for professionals working with individuals with psychiatric difficulties, its characterization of the Autism Spectrum holds significant sway. We will suggest Extended Mind and Enactive Cognition Theories, which theorize that mind (or cognition) is embodied and environmentally embedded, as coherent conceptual and theoretical spaces within which to investigate the possibility that certain repetitive behaviours exhibited by autistics possess functions or purposes that make them desirable. As lenses through which to re-examine ‘autism-related’ behavioral atypicalities, these theories not only open up explanatory possibilities underdeveloped in the research literature, but also cohere with how some autistics describe their own experience. Our position navigates a middle way between the view of autism as understood in terms of impairment, deficit and dysfunction and one that seeks to de-pathologize the Spectrum. In so doing we seek to contribute to a continuing dialogue between researchers, clinicians and self- or parent advocates. (shrink)

Knowledge representation and reasoning (KRR) is a fundamental area in artificial intelligence (AI) research, focusing on encoding world knowledge as logical formulae in ontologies. This formalism enables logic-based AI systems to deduce new insights from existing knowledge. Within KRR, description logics (DLs) are a prominent family of languages to represent knowledge formally. They are decidable fragments of first-order logic, and their models can be visualized as edge- and vertex-labeled directed binary graphs. DLs facilitate various reasoning tasks, including checking the satisfiability (...) of statements and deciding entailment. However, a significant challenge arises in the computation of models of DL ontologies in the context of explaining reasoning results. Although existing algorithms efficiently compute models for reasoning tasks, they usually do not consider aspects of human cognition, leading to models that may be less effective for explanatory purposes. This paper tackles this challenge by proposing an approach to enhance the intelligibility of models of DL ontologies for users. By integrating insights from cognitive science and philosophy, we aim to identify key graph properties that make models more accessible and useful for explanation. (shrink)

The relationship between the social sciences and the cognitive sciences is underdeveloped and complicated, for reasons we will explain in this chapter, and the philosophical discussion of this relationship has the same properties. Many reasons for the lack of development relate to a traditional philosophical issue: explanation. The explanatory structure of cognitive science reasoning and argumentation is unusual and difcult to t into the traditional model of scientic explanation, though they do relate, in an odd way, (...) to the traditional “reasons” explanations discussed in the philosophy of social science, through the notion of “folk psychology.” The cognitive science explanations themselves, as they relate to traditional “social science” topics, involve additional problems. They depend on a strategy of reducing complexity by beginning with those aspects of mind that can be most readily simplied, such as perception and body movements. Therefore, traditional social science topics, such as social interaction, which cannot be readily simplied, are something of an afterthought. (shrink)

Cognitive Science is a promising field of research that deals with one of the most fundamental questions ever: how do beings know? However, despite the long and extensive tradition of the field it has not yet become an area of knowledge with scientific identity. This is primarily due to three reasons: the lack of boundaries in defining the object of study, i.e. cognition, the lack of a precise, robust and consistent scientific methodology and results, and the inner problems derived (...) from its interdisciplinary nature. This paper presents a background review, a theoretical frame and a humble reflection on these topics in order to arouse the internal debate among readers once more. (shrink)

The paper critically examines some theses from A.V. Smirnov’s monograph ‘The Logic of Meaning as a Philosophy of Consciousness: An Invitation to Reflection’. In particular, the statement about the inability of cognitive sciences to exhaustively explain conscious­ness because of its de-subjectivation within their framework. It is shown that cognitive sciences are generally able to cope with the intellectual and controlling aspects of con­sciousness. Only its phenomenal aspect remains in question, but this is clearly not what (...) the author of the monograph means. Further, he argues that understanding the workings of consciousness underlies the philosophical foundations of any subject. The analysis shows that if we exclude consciousness as control and the phenomenal consciousness, which are obviously irrelevant here, then the philosophical foundations of anything within this understanding are reduced either to normative requirements in the form of the logical foundations of theories, or to empirical data in the form of cognitive limita­tions of real subjects. Attributing rationalism and universalism to the Western philosophy as its essential properties, the author of the monograph does not take into account that ra­tionalism as anti-empiricism has long been a kind of abandoned trend, and rationalism as a commitment to inferential procedures has also been recently challenged by some strong alternatives. Similarly, the author’s opinion of the Western philosophy of mind as the exe­cution of the Cartesian program, which he reduces to cogito ergo sum, is disputed. This methodological tool – and the metaphysical principle as well – of Descartes is subjected to incessant attacks from representatives of various schools of Western philosophy. More­over, it underlies not the philosophy of mind, but the epistemology of the great philoso­pher. Finally, the author’s concept of ‘unfolding the folded’ comes down to a kind of di­alectical deduction of the empirical features of various cultures from a priori predeter­mined ‘subject-predicate gluings’ and ‘intuitions of integrity’, which paradoxically brings us back to Hegelian-type rationalism. (shrink)

Behrendt's & Young's (B&Y's) persuasive scientific theory explains hallucinations, and is supported by a wide variety of psychological evidence, both normal and abnormal – unlike their philosophical thesis, Kantian idealism. I argue that the evidence cited by the authors in support of idealism actually favors realism. Fortunately, their scientific theory is separable from their philosophy, and is methodologically consistent with realism.