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

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  1. Aaron Sloman & David Vernon, A First Draft Analysis of Some Meta-Requirements for Cognitive Systems in Robots (An Exercise in Logical Topography Analysis. ).score: 90.0
    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. Tobias Matzner (forthcoming). The Model Gap: Cognitive Systems in Security Applications and Their Ethical Implications. [REVIEW] AI and Society:1-8.score: 90.0
    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. Michael Silberstein & Anthony Chemero (2012). Complexity and Extended Phenomenological‐Cognitive Systems. Topics in Cognitive Science 4 (1):35-50.score: 75.0
    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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  4. Noah Moss Brender (2013). Sense-Making and Symmetry-Breaking: Merleau-Ponty, Cognitive Science, and Dynamic Systems Theory. Symposium 17 (2):247-273.score: 72.0
    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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  5. Dilip Patel & Shushma Patel (2003). The Cognitive Process of Problem Solving: A Soft Systems Approach. [REVIEW] Brain and Mind 4 (2):283-295.score: 72.0
    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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  6. 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.score: 62.0
    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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  7. Ronald N. Giere (2004). The Problem of Agency in Scienti?C Distributed Cognitive Systems. Journal of Cognition and Culture 4 (3-4):759-774.score: 61.0
    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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  8. 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.score: 60.0
    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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  9. Colin Klein, Critical Notice: Cognitive Systems and the Extended Mind by Robert Rupert.score: 60.0
    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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  10. Ronald Giere, Models as Parts of Distributed Cognitive Systems.score: 60.0
    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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  11. Ronald N. Giere (2006). The Role of Agency in Distributed Cognitive Systems. Philosophy of Science 73 (5):710-719.score: 60.0
    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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  12. Robert D. Rupert (2009). Cognitive Systems and the Extended Mind. OUP USA.score: 60.0
    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 product 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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  13. Ron Sun & Gregg C. Oden, Integration of Cognitive Systems Across Disciplinary Boundaries.score: 60.0
    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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  14. Deborah P. Tollefsen, Rick Dale & Alexandra Paxton (2013). Alignment, Transactive Memory, and Collective Cognitive Systems. Review of Philosophy and Psychology 4 (1):49-64.score: 60.0
    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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  15. Uri Hershberg & Sol Efroni (2001). The Immune System and Other Cognitive Systems. Complexity 6 (5):14-21.score: 60.0
    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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  16. Dov M. Gabbay (2003). A Practical Logic of Cognitive Systems. North Holland.score: 60.0
    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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  17. Patrick Rebuschat, Martin Rohrmeier, John A. Hawkins & Ian Cross (eds.) (2011). Language and Music as Cognitive Systems. OUP Oxford.score: 60.0
    The past 15 years have witnessed an increasing interest in the comparative study of language and music as cognitive systems. Language and music are uniquely human traits, so it is not surprising that this interest spans practically all branches of cognitive science, including psychology, computer science, linguistics, cognitive neuroscience, and education. Underlying the study of language and music is the assumption that the comparison of these two domains can shed light on the structural and functional properties (...)
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  18. Ron Chrisley, Brain Inspired Cognitive Systems (BICS).score: 60.0
    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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  19. John Fox (2011). Artificial Cognitive Systems: Where Does Argumentation Fit In? Behavioral and Brain Sciences 34 (2):78-79.score: 60.0
    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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  20. 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.score: 60.0
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  21. G. Mallen (2013). Early Computer Models of Cognitive Systems and the Beginnings of Cognitive Systems Dynamics. Constructivist Foundations 9 (1):137-138.score: 60.0
    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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  22. Jack C. Lyons (2003). Lesion Studies, Spared Performance, and Cognitive Systems. Cortex 39 (1):145-7.score: 58.0
    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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  23. Michael E. McCullough, Robert Kurzban & Benjamin A. Tabak (2013). Cognitive Systems for Revenge and Forgiveness. Behavioral and Brain Sciences 1 (1):1-15.score: 58.0
    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 (including homicide, bodily harm, theft, mate poaching, cuckoldry, reputational damage, sexual aggression, and the infliction of these costs on one's offspring, mates, coalition partners, or friends). One solution to this problem is to impose retaliatory costs on an aggressor so that the aggressor (...)
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  24. Terence E. Horgan & John L. Tienson (1992). Cognitive Systems as Dynamic Systems. Topoi 11 (1):27-43.score: 57.0
  25. Nancy J. Nersessian (2006). Model-Based Reasoning in Distributed Cognitive Systems. Philosophy of Science 73 (5):699-709.score: 57.0
    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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  26. Brian Fisher, Tera Marie Green & Richard Arias-Hernández (2011). Visual Analytics as a Translational Cognitive Science. Topics in Cognitive Science 3 (3):609-625.score: 57.0
    Visual analytics is a new interdisciplinary field of study that calls for a more structured scientific approach to understanding the effects of interaction with complex graphical displays on human cognitive processes. Its primary goal is to support the design and evaluation of graphical information systems that better support cognitive processes in areas as diverse as scientific research and emergency management. The methodologies that make up this new field are as yet ill defined. This paper proposes a pathway (...)
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  27. 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.score: 57.0
    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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  28. Roy Lachman (2004). Imposed Intelligibility and Strong Claims Concerning Cognitive Systems. Behavioral and Brain Sciences 27 (2):294-295.score: 57.0
    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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  29. 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.score: 57.0
    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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  30. Markus F. Peschl & Chris Stary (1998). The Role of Cognitive Modeling for User Interface Design Representations: An Epistemological Analysis of Knowledge Engineering in the Context of Human-Computer Interaction. [REVIEW] Minds and Machines 8 (2):203-236.score: 54.0
    In this paper we review some problems with traditional approaches for acquiring and representing knowledge in the context of developing user interfaces. Methodological implications for knowledge engineering and for human-computer interaction are studied. It turns out that in order to achieve the goal of developing human-oriented (in contrast to technology-oriented) human-computer interfaces developers have to develop sound knowledge of the structure and the representational dynamics of the cognitive system which is interacting with the computer.We show that in a first (...)
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  31. 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.score: 53.0
    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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  32. Orlin Vakarelov (2010). Pre-Cognitive Semantic Information. Knowledge, Technology & Policy 23 (2):193-226.score: 51.0
    This paper addresses one of the fundamental problems of the philosophy of information: How does semantic information emerge within the underlying dynamics of the world?—the dynamical semantic information problem. It suggests that the canonical approach to semantic information that defines data before meaning and meaning before use is inadequate for pre-cognitive information media. Instead, we should follow a pragmatic approach to information where one defines the notion of information system as a special kind of purposeful system emerging within the (...)
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  33. Alvaro Moreno, On What Makes Certain Dynamical Systems Cognitive: A Minimally Cognitive Organization Program.score: 51.0
    Dynamicism has provided cognitive science with important tools to understand some aspects of “how cognitive agents work” but the issue of “what makes something cognitive” has not been sufficiently addressed yet and, we argue, the former will never be complete without the latter. Behavioristic characterizations of cognitive properties are criticized in favor of an organizational approach focused on the internal dynamic relationships that constitute cognitive systems. A definition of cognition as adaptive-autonomy in the embodied (...)
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  34. Robert D. Rupert (2011). Cognitive Systems and the Supersized Mind. [REVIEW] Philosophical Studies 152 (3):427 - 436.score: 48.0
    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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  35. Robert D. Rupert (2010). Systems, Functions, and Intrinsic Natures: On Adams and Aizawa's The Bounds of Cognition. [REVIEW] Philosophical Psychology 23 (1):113-123.score: 48.0
  36. Karola Stotz (2010). Human Nature and Cognitive–Developmental Niche Construction. Phenomenology and the Cognitive Sciences 9 (4):483-501.score: 48.0
    Recent theories in cognitive science have begun to focus on the active role of organisms in shaping their own environment, and the role of these environmental resources for cognition. Approaches such as situated, embedded, ecological, distributed and particularly extended cognition look beyond ‘what is inside your head’ to the old Gibsonian question of ‘what your head is inside of’ and with which it forms a wider whole—its internal and external cognitive niche. Since these views have been treated as (...)
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  37. Anthony P. Atkinson, Wholes and Their Parts in Cognitive Psychology: Systems, Subsystems and Persons.score: 48.0
    Decompositional analysis is the process of constructing explanations of the characteristics of whole systems in terms of characteristics of parts of those whole systems. Cognitive psychology is an endeavour that develops explanations of the capacities of the human organism in terms of descriptions of the brain's functionally defined information-processing components. This paper details the nature of this explanatory strategy, known as functional analysis. Functional analysis is contrasted with two other varieties of decompositional analysis, namely, structural analysis and (...)
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  38. E. Thomas Lawson & Robert N. McCauley, The Cognitive Representation of Religious Ritual Form: A Theory of Participants' Competence with Their Religious Ritual Systems.score: 48.0
    Theorizing about religious ritual systems from a cognitive viewpoint involves (1) modeling cognitive processes and their products and (2) demonstrating their influence on religious behavior. Particularly important for such an approach to the study of religious ritual is the modeling of participants' representations of ritual form. In pursuit of that goal, we presented in Rethinking Religion a theory of religious ritual form that involved two commitments. The theory’s first commitment is that the cognitive apparatus for the (...)
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  39. Gennaro Auletta (2011). Cognitive Biology: Dealing with Information From Bacteria to Minds. Oxford University Press, Usa.score: 48.0
    Machine generated contents note: -- 1. Quantum Mechanics as a General Framework -- 2. Classical and Quantum Information and Entropy -- 3. The Brain: An Outlook -- 4. Vision -- 5. Dealing with Target's Motion and Our Own Movement -- 6. Complexity: A Necessary Condition -- 7. General Features of Life -- 8. The Organism as a Semiotic and Cybernetic System -- 9. Phylogeny -- 10. Ontogeny -- 11. Epigeny -- 12. Representational Semiotics -- 13. The Brain as an Information-Control (...)
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  40. Lorenzo Magnani (2009). Beyond Mind: How Brains Make Up Artificial Cognitive Systems. [REVIEW] Minds and Machines 19 (4):477-493.score: 48.0
    What I call semiotic brains are brains that make up a series of signs and that are engaged in making or manifesting or reacting to a series of signs: through this semiotic activity they are at the same time engaged in “being minds” and so in thinking intelligently. An important effect of this semiotic activity of brains is a continuous process of disembodiment of mind that exhibits a new cognitive perspective on the mechanisms underling the semiotic emergence of meaning (...)
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  41. Wilfried Sieg, Formal Systems, Church Turing Thesis, and Gödel's Theorems: Three Contributions to The MIT Encyclopedias of Cognitive Science.score: 48.0
    Wilfried Sieg. Formal Systems, Church Turing Thesis, and Gödel's Theorems: Three Contributions to The MIT Encyclopedias of Cognitive Science.
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  42. Ron Sun (2001). Cognitive Science Meets Multi-Agent Systems: A Prolegomenon. Philosophical Psychology 14 (1):5 – 28.score: 48.0
    In the current research on multi-agent systems (MAS), many theoretical issues related to sociocultural processes have been touched upon. These issues are in fact intellectually profound and should prove to be significant for MAS. Moreover, these issues should have equally significant impact on cognitive science, if we ever try to understand cognition in the broad context of sociocultural environments in which cognitive agents exist. Furthermore, cognitive models as studied in cognitive science can help us in (...)
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  43. Anthony P. Atkinson (1998). Systems, Subsystems and Persons: The Explanatory Scope of Cognitive Psychology. Acta Analytica 20 (20):43-60.score: 48.0
  44. Richard Cooper & Bradley Franks (1993). Interruptibility as a Constraint on Hybrid Systems. Minds and Machines 3 (1):73-96.score: 48.0
    It is widely mooted that a plausible computational cognitive model should involve both symbolic and connectionist components. However, sound principles for combining these components within a hybrid system are currently lacking; the design of such systems is oftenad hoc. In an attempt to ameliorate this we provide a framework of types of hybrid systems and constraints therein, within which to explore the issues. In particular, we suggest the use of system independent constraints, whose source lies in general (...)
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  45. Wilson S. Geisler & Randy L. Diehl (2003). A Bayesian Approach to the Evolution of Perceptual and Cognitive Systems. Cognitive Science 27 (3):379-402.score: 48.0
  46. 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.score: 48.0
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  47. Melanie Stollstorff, Yuko Munakata, Arielle Pc Jensen, Ryan Mori Guild, Harry Robert Smolker, Joseph M. Devaney & Marie T. Banich (2013). Individual Differences in Emotion-Cognition Interactions: Emotional Valence Interacts with Serotonin Transporter Genotype to Influence Brain Systems Involved in Emotional Reactivity and Cognitive Control. Frontiers in Human Neuroscience 7:327.score: 48.0
    The serotonin transporter gene (5-HTTLPR) influences emotional reactivity and attentional bias towards or away from emotional stimuli and has been implicated in psychopathological states, such as depression and anxiety disorder. The short allele is associated with increased reactivity and attention towards negatively-valenced emotional information, whereas the long allele is associated with that towards positively-valenced emotional information. The neural basis for individual differences in the ability to exert cognitive control over these bottom-up biases in emotional reactivity and attention is unknown, (...)
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  48. Heather K. J. van der Lely (2005). Domain-Specific Cognitive Systems: Insight From Grammatical-SLI. Trends in Cognitive Sciences 9 (2):53-59.score: 48.0
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  49. Robert A. Wilson (2010). Review of Robert D. Rupert, Cognitive Systems and the Extended Mind. [REVIEW] Notre Dame Philosophical Reviews 2010 (3).score: 47.0
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  50. Antoni Gomila (1995). From Cognitive Systems to Persons. In Android Epistemology. Cambridge: MIT Press.score: 47.0
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