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  1. Seiki Akama, Ed., Logic, Language and Computation Reviewed By.Barbara Abbott - 1998 - Philosophy in Review 18 (5):313-314.
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  2. Seiki Akama, Ed., Logic, Language and Computation. [REVIEW]Barbara Abbott - 1998 - Philosophy in Review 18:313-314.
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  3. Amorphous Computing.Harold Abelson & Nancy Forbes - 2000 - Complexity 5 (3):22.
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  4. Algebra of Approximate Computation.Karl Aberer - 1995 - In Erwin Engeler (ed.), The Combinatory Programme. Birkhäuser. pp. 77--96.
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  5. On Using Compressibility to Detect When Slime Mould Completed Computation.Andrew Adamatzky & Jeff Jones - 2016 - Complexity 21 (5):162-175.
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  6. Toward an Interpretation of Dynamic Neural Activity in Terms of Chaotic Dynamical Systems-Open Peer Commentary-Chaotic Neurons and Analog Computation.K. Aihara & J. K. Ryeu - 2001 - Behavioral and Brain Sciences 24 (5):810-810.
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  7. The Pledge of the Computing Professional: Recognizing and Promoting Ethics in the Computing Professions.Bill Albrecht, Ken Christensen, Venu Dasigi, Jim Huggins & Jody Paul - 2012 - Acm Sigcas Computers and Society 42 (1):6-8.
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  8. Toward Feasible and Efficient DNA Computation.Martyn Amos, Alan Gibbons & Paul E. Dunne - 1998 - Complexity 4 (1):20-24.
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  9. From Cooperative Computation to Man/Machine Symbiosis.Michael A. Arbib - 1993 - Behavioral and Brain Sciences 16 (4):748.
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  10. Levels of Modeling of Mechanisms of Visually Guided Behavior.Michael A. Arbib - 1987 - Behavioral and Brain Sciences 10 (3):407.
  11. From Analogue to Digital.Annabel Astbury - 2009 - Agora 44 (3):34.
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  12. Formal Signs and Numerical Computation: Between Intuitionism and Formalism. Critique of Computational Reason.Bruno Bachimont - 2008 - In Jan Lazardzig, Ludger Schwarte & Helmar Schramm (eds.), Theatrum Scientiarum - English Edition, Volume 2, Instruments in Art and Science: On the Architectonics of Cultural Boundaries in the 17th Century. De Gruyter. pp. 362-382.
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  13. Experimental Computation as an Ontological Game Changer: The Impact of Modern Mathematical Computation Tools on the Ontology of Mathematics.David H. Bailey & Jonathan M. Borwein - unknown
    Robust, concrete and abstract, mathematical computation and inference on the scale now becoming possible should change the discourse about many matters mathematical. These include: what mathematics is, how we know something, how we persuade each other, what suffices as a proof, the infinite, mathematical discovery or invention, and other such issues.
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  14. Recurring Models and Sensitivity to Computational Constraints.Anouk Barberousse & Cyrille Imbert - 2014 - The Monist 97 (3):259-279.
    Why are some models, like the harmonic oscillator, the Ising model, a few Hamiltonian equations in quantum mechanics, the poisson equation, or the Lokta-Volterra equations, repeatedly used within and across scientific domains, whereas theories allow for many more modeling possibilities? Some historians and philosophers of science have already proposed plausible explanations. For example, Kuhn and Cartwright point to a tendency toward conservatism in science, and Humphreys emphasizes the importance of the intractability of what he calls “templates.” This paper investigates more (...)
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  15. What is the Computational Goal of the Neocortex.H. B. Barlow - 1994 - In Christof Koch & J. Davis (eds.), Large-Scale Neuronal Theories of the Brain. MIT Press. pp. 1--22.
  16. Computational Modelling of Hydrogen Embrittlement in Welded Structures.O. Barrera & A. C. F. Cocks - 2013 - Philosophical Magazine 93 (20):2680-2700.
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  17. Recent Developments in Computing and Philosophy.Anthony F. Beavers - 2011 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 42 (2):385-397.
    Because the label "computing and philosophy" can seem like an ad hoc attempt to tie computing to philosophy, it is important to explain why it is not, what it studies (or does) and how it differs from research in, say, "computing and history," or "computing and biology". The American Association for History and Computing is "dedicated to the reasonable and productive marriage of history and computer technology for teaching, researching and representing history through scholarship and public history" (http://theaahc.org). More pervasive, (...)
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  18. Using Computational Models to Discover and Understand Mechanisms.William Bechtel - forthcoming - Studies in History and Philosophy of Science Part A.
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  19. The Practical Limitations on Computing.R. Becker - 1988 - South African Journal of Philosophy-Suid-Afrikaanse Tydskrif Vir Wysbegeerte 7 (2):66-72.
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  20. 18th Workshop on Logic, Language, Information and Computation (Wollic 2011).Lev Beklemishev, Ruy de Queiroz & Andre Scedrov - 2012 - Bulletin of Symbolic Logic 18 (1):152-153.
  21. Computing, and Consciousness.Meurig Beynon - 2011 - In David Clarke & Eric F. Clarke (eds.), Music and Consciousness: Philosophical, Psychological, and Cultural Perspectives. Oxford University Press. pp. 157.
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  22. The Decision Model of Information Processing in Situations with a Source of Reliable Information.Adam Biela - 1974 - Roczniki Filozoficzne 22 (4):115.
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  23. For Learning by Imitation Computational Modeling.Aude Billard & Michael Arbib - 2002 - In Maxim I. Stamenov & Vittorio Gallese (eds.), Mirror Neurons and the Evolution of Brain and Language. John Benjamins. pp. 42--343.
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  24. The Scandal of Computation - What is Computation? - AISB Convention 2013.Mark J. Bishop & Yasemin Erden (eds.) - 2013 - AISB.
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  25. Symbols, Computation, and Intentionality.John Black - 1999 - Review of Metaphysics 52 (4):945-947.
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  26. Logic, Language and Computation, Volume 3.Patrick Blackburn, Nick Braisby, Lawrence Cavedon & Atsushi Shimojima (eds.) - 2001 - Center for the Study of Language and Inf.
    With the rise of the internet and the proliferation of technology to gather and organize data, our era has been defined as "the information age." With the prominence of information as a research concept, there has arisen an increasing appreciation of the intertwined nature of fields such as logic, linguistics, and computer science that answer the questions about information and the ways it can be processed. The many research traditions do not agree about the exact nature of information. By bringing (...)
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  27. A Computational Framework for Modelling Grain-Structure Evolution in Three Dimensions.Max O. Bloomfield, David F. Richards & Timothy S. Cale† - 2003 - Philosophical Magazine 83 (31-34):3549-3568.
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  28. An Evaluation of Computational Modeling in Cognitive Science.M. A. Boden - 2008 - In Ron Sun (ed.), The Cambridge Handbook of Computational Psychology. Cambridge University Press. pp. 667--683.
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  29. Computing and Creativity.Margaret A. Boden - 1998 - In Terrell Ward Bynum & James Moor (eds.), The Digital Phoenix: How Computers Are Changing Philosophy. Blackwell.
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  30. Complexity and the Paradigm of Wolfram's A New Kind of Science: From the Computational Sciences to the Science of Computation.Kovas Boguta - 2005 - Complexity 10 (4):15-21.
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  31. Real Algorithms: A Defense of Cognitivism.John Bolender - 1998 - Philosophical Inquiry 20 (3-4):41-58.
    John Searle dismisses the attempt to understand thought as a form of computation, on the grounds that it is not scientific. Science is concerned with intrinsic properties, i.e. those features which are not observer relative, e.g. science is concerned with mass but not with beauty. Computation, according to Searle, presupposes the property of following an algorithm, but algorithmicity is normative, by reason of appealing to function, and hence not intrinsic. I argue that Searle's critique presupposes the folk notion of function, (...)
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  32. Justification Logic as a Foundation for Certifying Mobile Computation.Eduardo Bonelli & Federico Feller - 2012 - Annals of Pure and Applied Logic 163 (7):935-950.
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  33. Inleiding: 'History of Computing'. Geschiedschrijving Over Computers En Computergebruik in Nederland.Adrienne van den Boogaard - 2008 - Studium 1 (2):89.
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  34. Abstract State Machines: A Unifying View of Models of Computation and of System Design Frameworks.Egon Börger - 2005 - Annals of Pure and Applied Logic 133 (1-3):149-171.
    We capture the principal models of computation and specification in the literature by a uniform set of transparent mathematical descriptions which—starting from scratch—provide the conceptual basis for a comparative study.1.
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  35. 14th Workshop on Logic, Language, Information and Computation (Wollic 2007).Alex Borgida & Alessandra Carbone - 2008 - Bulletin of Symbolic Logic 14 (1):160-161.
  36. Models and People: An Alternative View of the Emergent Properties of Computational Models.Fabio Boschetti - 2016 - Complexity 21 (6):202-213.
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  37. Causality, Emergence, Computation and Unreasonable Expectations.Fabio Boschetti - 2011 - Synthese 181 (3):405-412.
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  38. What Do Parallel Fibers Do?James M. Bower - 1997 - Behavioral and Brain Sciences 20 (2):247-247.
    Braitenberg et al.'s proposal, like most previous theories of cerebellar function (see Bower 1997, for review), is fundamentally based on the striking geometric relationship between parallel fibers and Purkinje cells. As in previous models, the current theory assumes that the activation of granule cells results in a of activated Purkinje cells, although it adds the new requirement that the granule cell layer itself have a particular spatial/temporal pattern of activation. I believe there is clear evidence that parallel fibers do not (...)
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  39. Computing, Design, Art: Reflections on an Innovative Moment in History.Stephen Boyd Davis & Simone Gristwood - 2016 - In .
    The chapter is concerned with the role of art and design in the history and philosophy of computing, and the role of computing in models of design and art. It offers insights arising from research into a period in the 1960s and 70s, particularly in the UK, when computing became more available to artists and designers, focusing on Bruce Archer and John Lansdown in London. It suggests that models of computing interacted with conceptualisations of art, design and creative activities in (...)
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  40. A Mechanical Proof of the Unsolvability of the Halting Problem.Robert Boyer - unknown
    We describe a proof by a computer program of the unsolvability of the halting problem. The halting problem is posed in a constructive, formal language. The computational paradigm formalized is Pure LISP, not Turing machines. The machine was led to the proof by the authors, who suggested certain function definitions and stated certain intermediate lemmas. The machine checked that every suggested definition was admissible and the machine proved the main theorem and every lemma. We believe this is the first instance (...)
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  41. Computing 'What' and 'Where' in the Visual System.OJ Braddick - unknown
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  42. AI and the Turing Model of Computation.Thomas M. Breuel - 1990 - Behavioral and Brain Sciences 13 (4):657.
  43. Phenomenological Computation?Søren Brier - 2014 - Constructivist Foundations 9 (2):234-235.
    Open peer commentary on the article “Info-computational Constructivism and Cognition” by Gordana Dodig-Crnkovic. Upshot: The main problems with info-computationalism are: (1) Its basic concept of natural computing has neither been defined theoretically or implemented practically. (2. It cannot encompass human concepts of subjective experience and intersubjective meaningful communication, which prevents it from being genuinely transdisciplinary. (3) Philosophically, it does not sufficiently accept the deep ontological differences between various paradigms such as von Foerster’s second- order cybernetics and Maturana and Varela’s theory (...)
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  44. Representation in Digital Systems.A. Briggle - 2008 - In P. Brey, A. Briggle & K. Waelbers (eds.), Current Issues in Computing and Philosophy. Ios Press. pp. 175--116.
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  45. Current Issues in Computing and Philosophy.Adam Briggle, Katinka Waelbers & Brey Philip (eds.) - 2008 - IOS Press.
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  46. Encoding, Decoding, and Central Functions in Human Information Processing.George E. Briggs & James M. Swanson - 1970 - Journal of Experimental Psychology 86 (2):296.
  47. Philosophy and 'Super'computation.Sehner Bringsjord - 1998 - In T. W. Bynum & J. Moor (eds.), The Digital Phoenix. Cambridge: Blackwell. pp. 231--252.
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  48. Entrepreneurial IT in the Age of Smart Machines.Selmer Bringsjord - unknown
    Don’t Bury Your Head in the Sand! • Some say: “AI is dead.” (Or: “AI is dying.”) • This is due to either self-deception or what Turing — the grandfather of computer sci-.
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  49. Explaining Phi Without Dennett's Exotica: Good Ol' Computation Suffices.Selmer Bringsjord - manuscript
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  50. Toward a Formal Philosophy of Hypercomputation.Selmer Bringsjord & Michael Zenzen - 2002 - Minds and Machines 12 (2):241-258.
    Does what guides a pastry chef stand on par, from the standpoint of contemporary computer science, with what guides a supercomputer? Did Betty Crocker, when telling us how to bake a cake, provide an effective procedure, in the sense of `effective' used in computer science? According to Cleland, the answer in both cases is ``Yes''. One consequence of Cleland's affirmative answer is supposed to be that hypercomputation is, to use her phrase, ``theoretically viable''. Unfortunately, though we applaud Cleland's ``gadfly philosophizing'' (...)
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