Search results for 'Cognitive systems' (try it on Scholar)

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  1.  51
    Aaron Sloman & David Vernon, A First Draft Analysis of Some Meta-Requirements for Cognitive Systems in Robots (An Exercise in Logical Topography Analysis. ).
    This is a contribution to construction of a research roadmap for future cognitive systems, including intelligent robots, in the context of the euCognition network, and UKCRC Grand Challenge 5: Architecture of Brain and Mind. -/- A meeting on the euCognition roadmap project was held at Munich Airport on 11th Jan 2007. This document was in part a response to discussions at that meeting. An explanation of why specifying requirements is a hard problem, and why it needs to be (...)
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  2.  8
    Tobias Matzner (2016). The Model Gap: Cognitive Systems in Security Applications and Their Ethical Implications. [REVIEW] AI and Society 31 (1):95-102.
    The use of cognitive systems like pattern recognition or video tracking technology in security applications is becoming ever more common. The paper considers cases in which the cognitive systems are meant to assist human tasks by providing information, but the final decision is left to the human. All these systems and their various applications have a common feature: an intrinsic difference in how a situation or an event is assessed by a human being and a (...)
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  3.  30
    Robert D. Rupert (2009). Cognitive Systems and the Extended Mind. OUP Usa.
    Robert Rupert argues against the view that human cognitive processes comprise elements beyond the boundary of the organism, developing a systems-based conception in place of this extended view. He also argues for a conciliatory understanding of the relation between the computational approach to cognition and the embedded and embodied views.
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  4.  54
    Vincent C. Müller (2012). Autonomous Cognitive Systems in Real-World Environments: Less Control, More Flexibility and Better Interaction. Cognitive Computation 4 (3):212-215.
    In October 2011, the “2nd European Network for Cognitive Systems, Robotics and Interaction”, EUCogII, held its meeting in Groningen on “Autonomous activity in real-world environments”, organized by Tjeerd Andringa and myself. This is a brief personal report on why we thought autonomy in real-world environments is central for cognitive systems research and what I think I learned about it. --- The theses that crystallized are that a) autonomy is a relative property and a matter of (...)
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  5.  49
    Antoni Gomila & Vincent C. Müller (2012). Challenges for Artificial Cognitive Systems. Journal of Cognitive Science 13 (4):452-469.
    The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we (...)
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  6. Adrian P. Banks & Lynne J. Millward (2009). Distributed Mental Models: Mental Models in Distributed Cognitive Systems. Journal of Mind and Behavior 30 (4):249-266.
    The function of groups as information processors is increasingly being recognised in a number of theories of group cognition. A theme of many of these is an emphasis on sharing cognition. This paper extends current conceptualisations of groups by critiquing the focus on shared cognition and emphasising the distribution of cognition in groups. In particular, it develops an account of the distribution of one cognitive construct, mental models. Mental models have been chosen as a focus because they are used (...)
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  7. Michael Silberstein & Anthony Chemero (2012). Complexity and Extended Phenomenological‐Cognitive Systems. Topics in Cognitive Science 4 (1):35-50.
    The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view of cognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to (...)
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  8.  9
    Larissa K. Samuelson, Gavin W. Jenkins & John P. Spencer (2015). Grounding Cognitive‐Level Processes in Behavior: The View From Dynamic Systems Theory. Topics in Cognitive Science 7 (2):191-205.
    Marr's seminal work laid out a program of research by specifying key questions for cognitive science at different levels of analysis. Because dynamic systems theory focuses on time and interdependence of components, DST research programs come to very different conclusions regarding the nature of cognitive change. We review a specific DST approach to cognitive-level processes: dynamic field theory. We review research applying DFT to several cognitive-level processes: object permanence, naming hierarchical categories, and inferring intent, that (...)
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  9. Noah Moss Brender (2013). Sense-Making and Symmetry-Breaking: Merleau-Ponty, Cognitive Science, and Dynamic Systems Theory. Symposium: The Canadian Journal of Continental Philosophy 17 (2):247-273.
    From his earliest work forward, phenomenologist Maurice Merleau-Ponty attempted to develop a new ontology of nature that would avoid the antinomies of realism and idealism by showing that nature has its own intrinsic sense which is prior to reflection. The key to this new ontology was the concept of form, which he appropriated from Gestalt psychology. However, Merleau-Ponty struggled to give a positive characterization of the phenomenon of form which would clarify its ontological status. Evan Thompson has recently taken up (...)
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  10.  20
    Dilip Patel & Shushma Patel (2003). The Cognitive Process of Problem Solving: A Soft Systems Approach. [REVIEW] Brain and Mind 4 (2):283-295.
    In this paper we describe the nature and problems of business and define one aspect of the business environment. We then propose a framework based on augmented soft systems methodology and object technology that captures both the soft and hard aspects of a business environment within the context of organisational culture. We also briefly discuss cognitive informatics and its relevance to understanding problems and solutions. Pólya's work, which is based around solving mathematical problems, is considered within the context (...)
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  11.  1
    Leonard Talmy (2014). Relating Language to Other Cognitive Systems: An Abridged Account. Cosmos and History: The Journal of Natural and Social Philosophy 10 (1):211-226.
    An important research direction in cognitive science consists of cross-comparing the forms of organization exhibited by different cognitive systems, with the long-range aim of ascertaining the overall character of human cognitive organization. Relatively distinct major cognitive systems of this sort would seem to include: perception, motor control, affect, reasoning, language, and cultural structure. The general finding is that some properties of organization are shown by only one system, some by several, and some by all. (...)
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  12.  25
    Deborah P. Tollefsen, Rick Dale & Alexandra Paxton (2013). Alignment, Transactive Memory, and Collective Cognitive Systems. Review of Philosophy and Psychology 4 (1):49-64.
    Research on linguistic interaction suggests that two or more individuals can sometimes form adaptive and cohesive systems. We describe an “alignment system” as a loosely interconnected set of cognitive processes that facilitate social interactions. As a dynamic, multi-component system, it is responsive to higher-level cognitive states such as shared beliefs and intentions (those involving collective intentionality) but can also give rise to such shared cognitive states via bottom-up processes. As an example of putative group cognition we (...)
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  13.  5
    Patrick Rebuschat, Martin Rohrmeier, John A. Hawkins & Ian Cross (eds.) (2011). Language and Music as Cognitive Systems. OUP Oxford.
    The past 15 years have witnessed an increasing interest in the comparative study of language and music as cognitive systems. This book presents an interdisciplinary study of language and music, exploring the following core areas - structural comparisons, evolution, learning and processing, and neuroscience.
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  14.  59
    Ronald N. Giere (2006). The Role of Agency in Distributed Cognitive Systems. Philosophy of Science 73 (5):710-719.
    In previous publications I have argued that much scientific activity should be thought of as involving the operation of distributed cognitive systems. Since these contributions to the cognitive study of science appear in venues not necessarily frequented by philosophers of science, I begin with a brief introduction to the notion of a distributed cognitive system. I then describe what I take to be an exemplary case of a scientific distributed cognitive system, the Hubble Space Telescope (...)
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  15. James Blair, A. A. Marsh, E. Finger, K. S. Blair & J. Luo (2006). Neuro-Cognitive Systems Involved in Morality. Philosophical Explorations 9 (1):13 – 27.
    In this paper, we will consider the neuro-cognitive systems involved in mediating morality. Five main claims will be made. First, that there are multiple, partially separable neuro-cognitive architectures that mediate specific aspects of morality: social convention, care-based morality, disgust-based morality and fairness/justice. Second, that all aspects of morality, including social convention, involve affect. Third, that the neural system particularly important for social convention, given its role in mediating anger and responding to angry expressions, is ventrolateral prefrontal cortex. (...)
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  16.  64
    Ronald N. Giere (2004). The Problem of Agency in Scienti?C Distributed Cognitive Systems. Journal of Cognition and Culture 4 (3-4):759-774.
    From the perspective of cognitive science, it is illuminating to think of much contemporary scienti?c research as taking place in distributed cognitive systems. This is particularly true of large-scale experimental and observational systems such as the Hubble Telescope. Clark, Hutchins, Knorr-Cetina, and Latour insist or imply such a move requires expanding our notions of knowledge, mind, and even consciousness. Whether this is correct seems to me not a straightforward factual question. Rather, the issue seems to be (...)
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  17. Colin Klein, Critical Notice: Cognitive Systems and the Extended Mind by Robert Rupert.
    Robert Rupert is well-known as an vigorous opponent of the hypothesis of extended cognition (HEC). His Cognitive Systems and the Extended Mind is a first-rate development of his “systems-based” approach to demarcating the mind. The results are impressive. Rupert’s account brings much-needed clarity to the often-frustrating debate over HEC: much more than just an attack on HEC, he gives a compelling picture of why the debate matters.
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  18.  67
    Ronald Giere, Models as Parts of Distributed Cognitive Systems.
    Recent work on the role of models in science has revealed a great many kinds of models performing many different roles. In this paper I suggest that one can find much unity among all this diversity by thinking of many models as being components of distributed cognitive systems. I begin by distinguishing the relevant notion of a distributed cognitive system and then give examples of different kinds of models that can be thought of as functioning as components (...)
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  19.  13
    Eliano Pessa & Graziano Terenzi (2007). Semiosis in Cognitive Systems: A Neural Approach to the Problem of Meaning. [REVIEW] Mind and Society 6 (2):189-209.
    This paper deals with the problem of understanding semiosis and meaning in cognitive systems. To this aim we argue for a unified two-factor account according to which both external and internal information are non-independent aspects of meaning, thus contributing as a whole in determining its nature. To overcome the difficulties stemming from this approach we put forward a theoretical scheme based on the definition of a suitable representation space endowed with a set of transformations, and we show how (...)
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  20.  7
    Usha Gosvvarni (2011). Language, Music, and Children's Brains: A Rhythmic Timing Perspective on Language and Music as Cognitive Systems. In Patrick Rebuschat, Martin Rohrmeier, John A. Hawkins & Ian Cross (eds.), Language and Music as Cognitive Systems. OUP Oxford 292.
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  21.  19
    Uri Hershberg & Sol Efroni (2001). The Immune System and Other Cognitive Systems. Complexity 6 (5):14-21.
    In the following pages we propose a theory on cognitive systems and the common strategies of perception, which are at the basis of their function. We demonstrate that these strategies are easily seen to be in place in known cognitive systems such as vision and language. Furthermore we show that taking these strategies into consideration implies a new outlook on immune function calling for a new appraisal of the immune system as a cognitive system.
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  22.  18
    Ron Sun & Gregg C. Oden, Integration of Cognitive Systems Across Disciplinary Boundaries.
    The present issue is the beginning of a new journal from various sub-disciplines and paradigms in order – Cognitive Systems Research – which we have to construct a coherent picture of how the various developed in response to what we perceive to be an pieces fit together overall. Such a synthesis is unfilled niche in the current literature in the areas of essential to the discovery of designs for general Cognitive Science and Artificial Intelligence.
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  23.  2
    John Fox (2011). Artificial Cognitive Systems: Where Does Argumentation Fit In? Behavioral and Brain Sciences 34 (2):78-79.
    Mercier and Sperber (M&S) suggest that human reasoning is reflective and has evolved to support social interaction. Cognitive agents benefit from being able to reflect on their beliefs whether they are acting alone or socially. A formal framework for argumentation that has emerged from research on artificial cognitive systems that parallels M&S's proposals may shed light on mental processes that underpin social interactions.
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  24.  5
    Ron Chrisley, Brain Inspired Cognitive Systems (BICS).
    This Neurocomputing special issue is based on selected, expanded and significantly revised versions of papers presented at the Second International Conference on Brain Inspired Cognitive Systems (BICS 2006) held at Lesvos, Greece, from 10 to 14 October 2006. The aim of BICS 2006, which followed the very successful first BICS 2004 held at Stirling, Scotland, was to bring together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological (...)
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  25.  1
    G. Mallen (2013). Early Computer Models of Cognitive Systems and the Beginnings of Cognitive Systems Dynamics. Constructivist Foundations 9 (1):137-138.
    Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: The target paper acknowledges some early computer modelling that I did in the years 1966–1968 when working with Pask at System Research Ltd in Richmond. In the commentary, I revisit the roots of this kind of modelling and follow the trajectory from then to today’s growing understanding of the dynamics of cognitive systems.
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  26. Robert D. Rupert (2009). Cognitive Systems and the Extended Mind. Oxford University Press Usa.
    Cognitive Systems and the Extended Mind surveys philosophical issues raised by the situated movement in cognitive science, that is, the treatment of cognitive phenomena as the joint products of brain, body, and environment. The book focuses primarily on the hypothesis of extended cognition, which asserts that human cognitive processes literally comprise elements beyond the boundary of the human organism. Rupert argues that the only plausible way in which to demarcate cognitions is systems-based: cognitive (...)
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  27. Robert D. Rupert (2010). Cognitive Systems and the Extended Mind. Oxford University Press Usa.
    Cognitive Systems and the Extended Mind surveys philosophical issues raised by the situated movement in cognitive science, that is, the treatment of cognitive phenomena as the joint products of brain, body, and environment. The book focuses primarily on the hypothesis of extended cognition, which asserts that human cognitive processes literally comprise elements beyond the boundary of the human organism. Rupert argues that the only plausible way in which to demarcate cognitions is systems-based: cognitive (...)
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  28.  8
    Dov M. Gabbay (2003). A Practical Logic of Cognitive Systems. North Holland.
    Agenda Relevance is the first volume in the authors' omnibus investigation of the logic of practical reasoning, under the collective title, A Practical Logic of Cognitive Systems. In this highly original approach, practical reasoning is identified as reasoning performed with comparatively few cognitive assets, including resources such as information, time and computational capacity. Unlike what is proposed in optimization models of human cognition, a practical reasoner lacks perfect information, boundless time and unconstrained access to computational complexity. The (...)
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  29. Colin Klein (2010). Cognitive Systems and the Extended Mind. [REVIEW] Journal of Mind and Behavior 31 (3-4).
    Robert Rupert is well-known as a vigorous opponent of the hypothesis of extended cognition . His Cognitive Systems and the Extended Mind is a first-rate development of his "systems-based" approach to demarcating the mind. The results are impressive. Rupert's account brings much-needed clarity to the often-frustrating debate over HEC: much more than just an attack on HEC, he gives a compelling picture of why the debate matters.
     
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  30. Robert D. Rupert (2010). Cognitive Systems and the Extended Mind. OUP Usa.
    COGNITIVE SYSTEMS AND THE EXTENDED MIND surveys philosophical issues raised by the situated movement in cognitive science, that is, the treatment of cognitive phenomena as the joint products of brain, body, and environment.
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  31.  16
    Michael E. McCullough, Robert Kurzban & Benjamin A. Tabak (2013). Cognitive Systems for Revenge and Forgiveness. Behavioral and Brain Sciences 36 (1):1-15.
    Minimizing the costs that others impose upon oneself and upon those in whom one has a fitness stake, such as kin and allies, is a key adaptive problem for many organisms. Our ancestors regularly faced such adaptive problems. One solution to this problem is to impose retaliatory costs on an aggressor so that the aggressor and other observers will lower their estimates of the net benefits to be gained from exploiting the retaliator in the future. We posit that humans have (...)
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  32.  36
    Nancy J. Nersessian (2006). Model-Based Reasoning in Distributed Cognitive Systems. Philosophy of Science 73 (5):699-709.
    This paper examines the nature of model-based reasoning in the interplay between theory and experiment in the context of biomedical engineering research laboratories, where problem solving involves using physical models. These "model systems" are sites of experimentation where in vitro models are used to screen, control, and simulate specific aspects of in vivo phenomena. As with all models, simulation devices are idealized representations, but they are also systems themselves, possessing engineering constraints. Drawing on research in contemporary cognitive (...)
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  33.  43
    Jack C. Lyons (2003). Lesion Studies, Spared Performance, and Cognitive Systems. Cortex 39 (1):145-7.
    The term ‘module’ has – to my ear – too many associations with Fodor’s (1983) seminal book, and I will concentrate here on the more general notion of a cognitive system. The latter, as I will understand the term, is – roughly – a computational mechanism which can operate independently of all other computational mechanisms (for a much fuller and more precise treatment, see Lyons, 2001). To say that there is a face recognition system, for example, is to say, (...)
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  34.  6
    Roy Lachman (2004). Imposed Intelligibility and Strong Claims Concerning Cognitive Systems. Behavioral and Brain Sciences 27 (2):294-295.
    The computational hypothesis was formulated with due concern for limits and is consistent with imposed intelligibility doctrines. Theories are products of scientific work that impose human classifications and formalisms on nature. The claim that “cognitive agents are dynamical systems” is untenable. Dynamical formalisms imposed on a natural system, given an approximate fit, serve as an explanatory framework and render a represented system predictable and intelligible.
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  35.  12
    Eric-Jan Wagenmakers, Han L. J. van der Maas & Simon Farrell (2012). Abstract Concepts Require Concrete Models: Why Cognitive Scientists Have Not Yet Embraced Nonlinearly Coupled, Dynamical, Self-Organized Critical, Synergistic, Scale-Free, Exquisitely Context-Sensitive, Interaction-Dominant, Multifractal, Interdependent Brain-Body-Niche Systems. Topics in Cognitive Science 4 (1):87-93.
    After more than 15 years of study, the 1/f noise or complex-systems approach to cognitive science has delivered promises of progress, colorful verbiage, and statistical analyses of phenomena whose relevance for cognition remains unclear. What the complex-systems approach has arguably failed to deliver are concrete insights about how people perceive, think, decide, and act. Without formal models that implement the proposed abstract concepts, the complex-systems approach to cognitive science runs the danger of becoming a philosophical (...)
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  36.  29
    Terence E. Horgan & John L. Tienson (1992). Cognitive Systems as Dynamic Systems. Topoi 11 (1):27-43.
  37.  13
    Daniel C. Dennett (1983). Intentional Systems in Cognitive Ethology: The 'Panglossian Paradigm' Defended. Behavioral and Brain Sciences 6 (3):343-90.
    Ethologists and others studying animal behavior in a spirit are in need of a descriptive language and method that are neither anachronistically bound by behaviorist scruples nor prematurely committed to particular Just such an interim descriptive method can be found in intentional system theory. The use of intentional system theory is illustrated with the case of the apparently communicative behavior of vervet monkeys. A way of using the theory to generate data - including usable, testable data - is sketched. The (...)
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  38.  21
    Istvan S. N. Berkeley (2001). Peter Novak, Mental Symbols: A Defence of the Classical Theory of Mind. Studies in Cognitive Systems 19, Dordrecht, Netherlands: Kluwer Academic Publishers, 1997, XXII + 266 Pp., $114.00, ISBN 0-7923-4370-. [REVIEW] Minds and Machines 11 (1):148-150.
  39.  17
    Larry Hauser (1997). Selmer Bringsjord, What Robots Can and Can't Be, Studies in Cognitive Systems. Minds and Machines 7 (3):433-438.
  40. Leib Litman & Mark Zelcer (2013). A Cognitive Neuroscience, Dual-Systems Approach to the Sorites Paradox. Journal of Experimental and Theoretical Artificial Intelligence 25 (3):355-366.
    Typical approaches to resolving the sorites paradox attempt to show, in one way or another, that the sorites argument is not paradoxical after all. However, if one can show that the sorites is not really paradoxical, the task remains of explaining why it appears to be a paradox. Our approach begins by addressing the appearance of paradox and then explores what this means for the paradox itself. We examine the sorites from the perspective of the various brain systems that (...)
     
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  41. Robert D. Rupert (2005). Minding One's Cognitive Systems: When Does a Group of Minds Constitute a Single Cognitive Unit? Episteme 1 (3):177-188.
    The possibility of group minds or group mental states has been considered by a number of authors addressing issues in social epistemology and related areas (Goldman 2004, Pettit 2003, Gilbert 2004, Hutchins 1995). An appeal to group minds might, in the end, do indispensable explanatory work in the social or cognitive sciences. I am skeptical, though, and this essay lays out some of the reasons for my skepticism. The concerns raised herein constitute challenges to the advocates of group minds (...)
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  42.  14
    S. Orestis Palermos (2014). Loops, Constitution and Cognitive Extension. Cognitive Systems Research 27:25-41.
    The ‘causal-constitution’ fallacy, the ‘cognitive bloat’ worry, and the persisting theoretical confusion about the fundamental difference between the hypotheses of embedded (HEMC) and extended (HEC) cognition are three interrelated worries, whose common point—and the problem they accentuate—is the lack of a principled criterion of constitution. Attempting to address the ‘causal-constitution’ fallacy, mathematically oriented philosophers of mind have previously suggested that the presence of non-linear relations between the inner and the outer contributions is sufficient for cognitive extension. The abstract (...)
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  43. Robert D. Rupert (2011). Cognitive Systems and the Supersized Mind. [REVIEW] Philosophical Studies 152 (3):427 - 436.
    In Supersizing the Mind: Embodiment, Action, and Cognitive Extension (Clark, 2008), Andy Clark bolsters his case for the extended mind thesis and casts a critical eye on some related views for which he has less enthusiasm. To these ends, the book canvasses a wide range of empirical results concerning the subtle manner in which the human organism and its environment interact in the production of intelligent behavior. This fascinating research notwithstanding, Supersizing does little to assuage my skepticism about the (...)
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  44.  7
    Wilson S. Geisler & Randy L. Diehl (2003). A Bayesian Approach to the Evolution of Perceptual and Cognitive Systems. Cognitive Science 27 (3):379-402.
  45.  7
    Heather K. J. van der Lely (2005). Domain-Specific Cognitive Systems: Insight From Grammatical-SLI. Trends in Cognitive Sciences 9 (2):53-59.
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  46.  4
    Wai-Tat Fu (forthcoming). The Central Role of Heuristic Search in Cognitive Computation Systems. Minds and Machines:1-21.
    This paper focuses on the relation of heuristic search and level of intelligence in cognitive computation systems. The paper begins with a review of the fundamental properties of a cognitive computation system, which is defined generally as a control system that generates goal-directed actions in response to environmental inputs and constraints. An important property of cognitive computations is the need to process local cues in symbol structures to access and integrate distal knowledge to generate a response. (...)
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  47.  33
    Esposito Anna, Esposito Antonietta M., Hoffmann Rüdiger, Müller Vincent C. & Vinciarelli Alessandro (eds.) (2012). Cognitive Behavioural Systems. Springer.
    This book constitutes refereed proceedings of the COST 2102 International Training School on Cognitive Behavioural Systems held in Dresden, Germany, in February 2011. The 39 revised full papers presented were carefully reviewed and selected from various submissions. The volume presents new and original research results in the field of human-machine interaction inspired by cognitive behavioural human-human interaction features. The themes covered are on cognitive and computational social information processing, emotional and social believable Human-Computer Interaction (HCI) (...), behavioural and contextual analysis of interaction, embodiment, perception, linguistics, semantics and sentiment analysis in dialogues and interactions, algorithmic and computational issues for the automatic recognition and synthesis of emotional states. (shrink)
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  48. L. Magnani (2007). Semiotic Brains and Artificial Minds. How Brains Make Up Material Cognitive Systems. In R. Gudwin & J. Queiroz (eds.), Semiotics and Intelligent Systems Development. Idea Group Inc. 1--41.
     
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  49. William Bechtel (2001). Representations: From Neural Systems to Cognitive Systems. In William P. Bechtel, Pete Mandik, Jennifer Mundale & Robert S. Stufflebeam (eds.), Philosophy and the Neurosciences: A Reader. Blackwell
  50. Robert D. Rupert (2010). Representation in Extended Cognitive Systems : Does the Scaffolding of Language Extend the Mind? In Richard Menary (ed.), The Extended Mind. MIT Press
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