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  1. Theodore Bach (2012). Analogical Cognition: Applications in Epistemology and the Philosophy of Mind and Language. Philosophy Compass 7 (5):348-360.
    Analogical cognition refers to the ability to detect, process, and learn from relational similarities. The study of analogical and similarity cognition is widely considered one of the ‘success stories’ of cognitive science, exhibiting convergence across many disciplines on foundational questions. Given the centrality of analogy to mind and knowledge, it would benefit philosophers investigating topics in epistemology and the philosophies of mind and language to become familiar with empirical models of analogical cognition. The goal of this essay is to describe (...)
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  2. Rajendra Badgaiyan (2012). Nonconscious Processing and a Novel Target for Schizophrenia Research. Open Journal of Psychiatry 2:335-339.
  3. Alex Barber (1999). Individuals, Properties, and the Explicitness Hierarchy. Behavioral and Brain Sciences 22 (5):756-757.
    The scenario used by Dienes & Perner to show that individual representation can be implicit when property representation is explicit can be adapted to show that property representation can be implicit when individual representation is explicit. So there is no hierarchy of explicitness, contrary to their claim. There is a reading of the “implicit/explicit” distinction that does appear to exhibit an asymmetry parallel to that alleged to hold between individual and property. But this is not a distinction Dienes & Perner (...)
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  4. William Bechtel (2009). Explanation: Mechanism, Modularity, and Situated Cognition. In Murat Aydede & P. Robbins (eds.), The Cambridge Handbook of Situated Cognition. Cambridge 155--170.
  5. Istvan S. Berkeley (2008). What the <0.70, 1.17, 0.99, 1.07> is a Symbol? Minds and Machines 18 (1):93-105.
    The notion of a ‘symbol’ plays an important role in the disciplines of Philosophy, Psychology, Computer Science, and Cognitive Science. However, there is comparatively little agreement on how this notion is to be understood, either between disciplines, or even within particular disciplines. This paper does not attempt to defend some putatively ‘correct’ version of the concept of a ‘symbol.’ Rather, some terminological conventions are suggested, some constraints are proposed and a taxonomy of the kinds of issue that give rise to (...)
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  6. Myles Brand (ed.) (1986). The Representation Of Knowledge And Belief. Tucson: University Of Arizona Press.
  7. Richard A. Carlson (1999). Implicit Representation, Mental States, and Mental Processes. Behavioral and Brain Sciences 22 (5):761-762.
    Dienes & Perner's target article constitutes a significant advance in thinking about implicit knowledge. However, it largely neglects processing details and thus the time scale of mental states realizing propositional attitudes. Considering real-time processing raises questions about the possible brevity of implicit representation, the nature of processes that generate explicit knowledge, and the points of view from which knowledge may be represented. Understanding the propositional attitude analysis in terms of momentary mental states points the way toward answering these questions.
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  8. Andrew Carstairs-McCarthy (1999). Explicitness and Predication: A Risky Linkage. Behavioral and Brain Sciences 22 (5):762-763.
  9. Andy Clark (1991). In Defense of Explicit Rules. In William Ramsey, Stephen P. Stich & D. Rumelhart (eds.), Philosophy and Connectionist Theory. Lawrence Erlbaum
  10. R. Cummins (1986). Inexplicit Representation. In Myles Brand (ed.), The Representation of Knowledge and Belief. Tucson: University of Arizona Press
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  11. Robert C. Cummins (1986). Inexplicit Information. In Myles Brand & Robert M. Harnish (eds.), The Representation of Knowledge and Belief. University of Arizona Press
    A discussion of a number of ways that information can be present in a computer program without being explicitly represented.
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  12. Eddy J. Davelaar (2011). Processes Versus Representations: Cognitive Control as Emergent, Yet Componential. Topics in Cognitive Science 3 (2):247-252.
    In this commentary, I focus on the difference between processes and representations and how this distinction relates to the question of what is controlled. Despite some views that task switching is a prototypical control process, the analysis concludes that task switching depends on the task goal representation and that control processes are there to prevent goal representations from disintegrating. Over time, these processes become obsolete, leaving behind a representation that automatically controls task performance. The distinction between processes and representations relates (...)
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  13. Martin Davies (1995). Two Notions of Implicit Rules. Philosophical Perspectives 9:153-83.
  14. Daniel C. Dennett (1993). Review of F. Varela, E. Thompson and E. Rosch, The Embodied Mind. [REVIEW] American Journal of Psychology 106:121-126.
    Cognitive science, as an interdisciplinary school of thought, may have recently moved beyond the bandwagon stage onto the throne of orthodoxy, but it does not make a favorable first impression on many people. Familiar reactions on first encounters range from revulsion to condescending dismissal--very few faces in the crowd light up with the sense of "Aha! So that's how the mind works! Of course!" Cognitive science leaves something out, it seems; moreover, what it apparently leaves out is important, even precious. (...)
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  15. Julien Dutant (2015). Neil Gascoigne and Tim Thornton, Tacit Knowledge, Durham: Acumen, 2013, 210 Pp., £18.99 , ISBN 1844655466; £55 , ISBN 1844655458. [REVIEW] Dialectica 69 (4):621-623.
  16. Joseph S. Fulda (1993). Computer-Generated Art, Music, and Literature: Philosophical Conundrums. SIGART Bulletin 4 (1):6-7.
    Considers the question of the authorship of the works in the title from a /philosophical/, as opposed to legal, standpoint, using the sense-reference dichotomy, intension-extension dichotomy, and procedural knowledge-declarative knowledge dichotomy. Reaches no conclusion.
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  17. Joseph S. Fulda (1988). The Logic of Expert Judging Systems and the Rights of the Accused. AI and Society 2 (3):266-269.
    Deals with the problem of enthymemes in expert systems designed to model legal reasoning; suggests that interactivity is crucial.
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  18. Nagarjuna G. (2009). Collaborative Creation of Teaching-Learning Sequences and an Atlas of Knowledge. Mathematics Teaching-Research Journal Online 3 (N3):23-40.
    Our focus in the article is to introduce a simple methodology of generating teaching-learning sequences using the semantic network techinque, followed by the emergent properties of such a network and their implications for the teaching-learning process (didactics) with marginal notes on epistemological implications. A collaborative portal for teachers, which publishes a network of prerequisites for teaching/learning any concept or an activity is introduced. The article ends with an appeal to the global community to contribute prerequisites of any subject to complete (...)
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  19. Anne von der Lieth Gardner (1987). An Artificial Intelligence Approach to Legal Reasoning. MIT Press.
  20. Neil Gascoigne & Tim Thornton (2013). Tacit Knowledge. Routledge.
    Tacit knowledge is the form of implicit knowledge that we rely on for learning. It is invoked in a wide range of intellectual inquiries, from traditional academic subjects to more pragmatically orientated investigations into the nature and transmission of skills and expertise. Notwithstanding its apparent pervasiveness, the notion of tacit knowledge is a complex and puzzling one. What is its status as knowledge? What is its relation to explicit knowledge? What does it mean to say that knowledge is tacit? Can (...)
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  21. Stephen Gaukroger, John Andrew Schuster & John Sutton (eds.) (2000). Descartes' Natural Philosophy. Routledge.
    Possibly the most comprehensive collection of essays on Descartes' scientific writings ever published, this volume offers a detailed reassessment of his scientific work and its bearing on his philosophy. The 35 essays, written by some of the world's leading scholars, cover topics as diverse as optics, cosmology and medicine. The collection looks at Descartes' work in the sciences as an aspect of his natural-philosophical agenda and discusses: the central place of medicine in Descartes' overall project; the connections between his investigations (...)
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  22. Richard Gelwick (2007). Fifty Years Of Discovering Personal Knowledge. Tradition and Discovery 34 (3):18-30.
    This address to The Polanyi Society’s June 13-15, 2008 conference at Loyola University in Chicago commemorates the fiftieth anniversary of Michael Polanyi ’s publication of Personal Knowledge and considers the generative influence of Polanyi ’s post-critical theory of knowledge that led to The Polany; Society, its journal Tradition & Discovery and more than 2000 books and papers on Polanyi ’s philosophy.
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  23. William M. Goodman (1985). Structures and Procedures. Philosophy Research Archives 11:551-578.
    This paper takes up the challenge which Carnap poses in his Aufbau: to make of it a basis for continued epistemological research. I try to close some gaps in Carnap’s original presentation and to make at least the first few steps of his constructional outline more accessible to the modern reader. Particularly emphasized is Carnap’s implicit recognition that, to be effective, “structural” models of epistemology (using logical symbols) must be complemented with “procedural” models (his “fictitious operations”). The paper shows how (...)
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  24. Robert F. Hadley (1995). The 'Explicit-Implicit' Distinction. Minds and Machines 5 (2):219-42.
    Much of traditional AI exemplifies the explicit representation paradigm, and during the late 1980''s a heated debate arose between the classical and connectionist camps as to whether beliefs and rules receive an explicit or implicit representation in human cognition. In a recent paper, Kirsh (1990) questions the coherence of the fundamental distinction underlying this debate. He argues that our basic intuitions concerning explicit and implicit representations are not only confused but inconsistent. Ultimately, Kirsh proposes a new formulation of the distinction, (...)
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  25. Robert F. Hadley (1993). Connectionism, Explicit Rules, and Symbolic Manipulation. Minds and Machines 3 (2):183-200.
    At present, the prevailing Connectionist methodology forrepresenting rules is toimplicitly embody rules in neurally-wired networks. That is, the methodology adopts the stance that rules must either be hard-wired or trained into neural structures, rather than represented via explicit symbolic structures. Even recent attempts to implementproduction systems within connectionist networks have assumed that condition-action rules (or rule schema) are to be embodied in thestructure of individual networks. Such networks must be grown or trained over a significant span of time. However, arguments (...)
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  26. Robert F. Hadley (1990). Connectionism, Rule-Following, and Symbolic Manipulation. Proc AAAI 3 (2):183-200.
  27. Jaap Hage & Bart Verheij (1994). Reason-Based Logic: A Logic for Reasoning with Rules and Reasons. Inform. Commun. Technol. Law 3 (2-3):171-209.
  28. Philip P. Hanson (ed.) (1990). Information, Language and Cognition. University of British Columbia Press.
  29. Jacobson Jacobson (1959). OLANYI'S Personal Knowledge; Towards a Post-Critical Philosophy. [REVIEW] Philosophy and Phenomenological Research 20:429.
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  30. David Kirsh (2003). Implicit and Explicit Representation. Encyclopedia of Cognitive Science 2:478–481.
    The degree to which information is encoded explicitly in a representation is related to the computational cost of recovering or using the information. Knowledge that is implicit in a system need not be represented at all, even implicitly, if the cost of recurring it is prohibitive.
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  31. David Kirsh (2003). Implicit and Explicit Representation. In L. Nadel (ed.), Implicit and Explicit Representation. Nature Publishing Group
    The degree to which information is encoded explicitly in a representation is related to the computational cost of recovering or using the information. Knowledge that is implicit in a system need not be represented at all, even implicitly, if the cost of recovering it is prohibitive.
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  32. David Kirsh (1990). When is Information Explicitly Represented? In Philip P. Hanson (ed.), Information, Language and Cognition. University of British Columbia Press
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  33. Antonio Lieto (2015). Some Epistemological Problems with the Knowledge Level in Cognitive Architectures. In Proceedings of AISC 2015, 12th Italian Conference on Cognitive Science, Genoa, 10-12 December 2015, Italy. NeaScience
    This article addresses an open problem in the area of cognitive systems and architectures: namely the problem of handling (in terms of processing and reasoning capabilities) complex knowledge structures that can be at least plausibly comparable, both in terms of size and of typology of the encoded information, to the knowledge that humans process daily for executing everyday activities. Handling a huge amount of knowledge, and selectively retrieve it according to the needs emerging in different situational scenarios, is an important (...)
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  34. Antonio Lieto (2014). A Computational Framework for Concept Representation in Cognitive Systems and Architectures: Concepts as Heterogeneous Proxytypes. Proceedings of 5th International Conference on Biologically Inspired Cognitive Architectures, Boston, MIT, Pocedia Computer Science, Elsevier:1-9.
    In this paper a possible general framework for the representation of concepts in cognitive artificial systems and cognitive architectures is proposed. The framework is inspired by the so called proxytype theory of concepts and combines it with the heterogeneity approach to concept representations, according to which concepts do not constitute a unitary phenomenon. The contribution of the paper is twofold: on one hand, it aims at providing a novel theoretical hypothesis for the debate about concepts in cognitive sciences by providing (...)
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  35. Antonio Lieto, Daniele Radicioni & Valentina Rho (forthcoming). Dual PECCS: A Cognitive System for Conceptual Representation and Categorization. Journal of Experimental and Theoretical Artificial Intelligence.
    In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual (...)
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  36. R. P. Loui & Jeff Norman (1995). Rationales and Argument Moves. Artificial Intelligence and Law 3 (3):159-189.
    We discuss five kinds of representations of rationales and provide a formal account of how they can alter disputation. The formal model of disputation is derived from recent work in argument. The five kinds of rationales are compilation rationales, which can be represented without assuming domain-knowledge (such as utilities) beyond that normally required for argument. The principal thesis is that such rationales can be analyzed in a framework of argument not too different from what AI already has. The result is (...)
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  37. Edward Mackinnon (1958). POLANYI, MICHAEL. "Personal Knowledge". [REVIEW] Modern Schoolman 36:294.
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  38. Eric Mandelbaum (2016). Attitude, Inference, Association: On the Propositional Structure of Implicit Bias. Noûs 50 (3):629-658.
    The overwhelming majority of those who theorize about implicit biases posit that these biases are caused by some sort of association. However, what exactly this claim amounts to is rarely specified. In this paper, I distinguish between different understandings of association, and I argue that the crucial senses of association for elucidating implicit bias are the cognitive structure and mental process senses. A hypothesis is subsequently derived: if associations really underpin implicit biases, then implicit biases should be modulated by counterconditioning (...)
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  39. Fernando Martínez & Jesús Ezquerro Martínez (1998). Explicitness with Psychological Ground. Minds and Machines 8 (3):353-374.
    Explicitness has usually been approached from two points of view, labelled by Kirsh the structural and the process view, that hold opposite assumptions to determine when information is explicit. In this paper, we offer an intermediate view that retains intuitions from both of them. We establish three conditions for explicit information that preserve a structural requirement, and a notion of explicitness as a continuous dimension. A problem with the former accounts was their disconnection with psychological work on the issue. We (...)
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  40. Christopher Menzel, Basic Semantic Integration. Semantic Interoperability and Integration, Proceedings of Dagstuhl Seminar 04391.
    The use of highly abstract mathematical frameworks is essential for building the sort of theoretical foundation for semantic integration needed to bring it to the level of a genuine engineering discipline. At the same time, much of the work that has been done by means of these frameworks assumes a certain amount of background knowledge in mathematics that a lot of people working in ontology, even at a fairly high theoretical level, lack. The major purpose of this short paper is (...)
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  41. Hugo Mercier (2012). The Social Functions of Explicit Coherence Evaluation. Mind and Society 11 (1):81-92.
    Coherence plays an important role in psychology. In this article, I suggest that coherence takes two main forms in humans’ cognitive system. The first belong to ‘system 1’. It relies on the degree of coherence between different representations to regulate them, without coherence being represented. By contrast other mechanisms, belonging to system 2, allow humans to represent the degree of coherence between different representations and to draw inferences from it. It is suggested that the mechanisms of explicit coherence evaluation have (...)
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  42. Alexander Miller (2014). Tacit Knowledge. International Journal of Philosophical Studies 22 (4):630-635.
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  43. Marco Mirolli (2012). Representations in Dynamical Embodied Agents: Re-Analyzing a Minimally Cognitive Model Agent. Cognitive Science 36 (5):870-895.
    Understanding the role of ‘‘representations’’ in cognitive science is a fundamental problem facing the emerging framework of embodied, situated, dynamical cognition. To make progress, I follow the approach proposed by an influential representational skeptic, Randall Beer: building artificial agents capable of minimally cognitive behaviors and assessing whether their internal states can be considered to involve representations. Hence, I operationalize the concept of representing as ‘‘standing in,’’ and I look for representations in embodied agents involved in simple categorization tasks. In a (...)
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  44. Edward C. Moore (1959). Book Review:Personal Knowledge: Towards a Post-Critical Philosophy Michael Polanyi. [REVIEW] Philosophy of Science 26 (3):270-.
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  45. Carlotta Pavese (2015). Practical Senses. Philosophers' Imprint 15 (29).
    In their theories of know how, proponents of Intellectualism routinely appeal to ‘practical modes of presentation’. But what are practical modes of presentation? And what makes them distinctively practical? In this essay, I develop a Fregean account of practical modes of presentation: I argue that there are such things as practical senses and I give a theory of what they are. One of the challenges facing the proponent of a distinctively Fregean construal of practical modes of presentation is to provide (...)
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  46. Josef Perner & Zoltan Dienes (1999). Deconstructing RTK: How to Explicate a Theory of Implicit Knowledge. Behavioral and Brain Sciences 22 (5):790-801.
    In this response, we start from first principles, building up our theory to show more precisely what assumptions we do and do not make about the representational nature of implicit and explicit knowledge (in contrast to the target article, where we started our exposition with a description of a fully fledged representational theory of knowledge (RTK). Along the way, we indicate how our analysis does not rely on linguistic representations but it implies that implicit knowledge is causally efficacious; we discuss (...)
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  47. Todd Peterson, Autonomous Learning of Sequential Tasks: Experiments and Analyses.
    This paper presents a novel learning model Clarion , which is a hybrid model based on the two-level approach proposed in Sun (1995). The model integrates neural, reinforcement, and symbolic learning methods to perform on-line, bottom-up learning (i.e., learning that goes from neural to symbolic representations). The model utilizes both procedural and declarative knowledge (in neural and symbolic representations respectively), tapping into the synergy of the two types of processes. It was applied to deal with sequential decision tasks. Experiments and (...)
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  48. William Ramsey, Stephen P. Stich & D. M. Rumelhart (eds.) (1991). Philosophy and Connectionist Theory. Lawrence Erlbaum.
    The philosophy of cognitive science has recently become one of the most exciting and fastest growing domains of philosophical inquiry and analysis. Until the early 1980s, nearly all of the models developed treated cognitive processes -- like problem solving, language comprehension, memory, and higher visual processing -- as rule-governed symbol manipulation. However, this situation has changed dramatically over the last half dozen years. In that period there has been an enormous shift of attention toward connectionist models of cognition that are (...)
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  49. Lawrence A. Shapiro, The Embodied Cognition Research Program.
    Unifying traditional cognitive science is the idea that thinking is a process of symbol manipulation, where symbols lead both a syntactic and a semantic life. The syntax of a symbol comprises those properties in virtue of which the symbol undergoes rule-dictated transformations. The semantics of a symbol constitute the symbolsÕ meaning or representational content. Thought consists in the syntactically determined manipulation of symbols, but in a way that respects their semantics. Thus, for instance, a calculating computer sensitive only to the (...)
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  50. Susanna Siegel (2015). Epistemic Evaluability and Perceptual Farce. In A. Raftopoulos (ed.), Cognitive Effects on Perception: New Philosophical Perspectives. Oxford
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