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  1. Barbara Abbott (1998). Seiki Akama, Ed., Logic, Language and Computation Reviewed By. Philosophy in Review 18 (5):313-314.
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  2. Barbara Abbott (1998). Seiki Akama, Ed., Logic, Language and Computation. [REVIEW] Philosophy in Review 18:313-314.
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  3. Harold Abelson & Nancy Forbes (2000). Amorphous Computing. Complexity 5 (3):22-25.
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  4. Karl Aberer (1995). Algebra of Approximate Computation. In Erwin Engeler (ed.), The Combinatory Programme. Birkhäuser. 77--96.
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  5. K. Aihara & J. K. Ryeu (2001). Toward an Interpretation of Dynamic Neural Activity in Terms of Chaotic Dynamical Systems-Open Peer Commentary-Chaotic Neurons and Analog Computation. Behavioral and Brain Sciences 24 (5):810-810.
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  6. Bill Albrecht, Ken Christensen, Venu Dasigi, Jim Huggins & Jody Paul (2012). The Pledge of the Computing Professional: Recognizing and Promoting Ethics in the Computing Professions. Acm Sigcas Computers and Society 42 (1):6-8.
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  7. Martyn Amos, Alan Gibbons & Paul E. Dunne (1998). Toward Feasible and Efficient DNA Computation. Complexity 4 (1):20-24.
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  8. Bruno Bachimont (2008). Formal Signs and Numerical Computation: Between Intuitionism and Formalism. Critique of Computational Reason. 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. 362-382.
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  9. H. B. Barlow (1994). What is the Computational Goal of the Neocortex. In Christof Koch & J. Davis (eds.), Large-Scale Neuronal Theories of the Brain. Mit Press. 1--22.
  10. R. Becker (1988). The Practical Limitations on Computing. South African Journal of Philosophy-Suid-Afrikaanse Tydskrif Vir Wysbegeerte 7 (2):66-72.
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  11. Lev Beklemishev, Ruy de Queiroz & Andre Scedrov (2012). 18th Workshop on Logic, Language, Information and Computation (Wollic 2011). Bulletin of Symbolic Logic 18 (1):152-153.
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  12. Meurig Beynon (2011). Computing, and Consciousness. In David Clarke & Eric F. Clarke (eds.), Music and Consciousness: Philosophical, Psychological, and Cultural Perspectives. Oxford University Press. 157.
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  13. John Black (1999). Symbols, Computation, and Intentionality. Review of Metaphysics 52 (4):945-947.
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  14. Patrick Blackburn, Nick Braisby, Lawrence Cavedon & Atsushi Shimojima (eds.) (2001). Logic, Language and Computation, Volume 3. Center for the Study of Language and Inf.
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  15. M. A. Boden (2008). An Evaluation of Computational Modeling in Cognitive Science. In Ron Sun (ed.), The Cambridge Handbook of Computational Psychology. Cambridge University Press. 667--683.
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  16. Kovas Boguta (2005). Complexity and the Paradigm of Wolfram's A New Kind of Science: From the Computational Sciences to the Science of Computation. Complexity 10 (4):15-21.
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  17. Eduardo Bonelli & Federico Feller (2012). Justification Logic as a Foundation for Certifying Mobile Computation. Annals of Pure and Applied Logic 163 (7):935-950.
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  18. A. Briggle (2008). Representation in Digital Systems. In P. Brey, A. Briggle & K. Waelbers (eds.), Current Issues in Computing and Philosophy. Ios Press. 175--116.
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  19. Sehner Bringsjord (1998). Philosophy and 'Super'computation. In T. W. Bynum & J. Moor (eds.), The Digital Phoenix. Cambridge: Blackwell. 231--252.
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  20. Selmer Bringsjord, Explaining Phi Without Dennett's Exotica: Good Ol' Computation Suffices.
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  21. Selmer Bringsjord & Michael Zenzen (2002). Toward a Formal Philosophy of Hypercomputation. 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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  22. Stephen D. Brown, Robert J. Francis, Jonathan Rose & Zvonko G. Vranesic (1992). Field-Programmable Gate Arrays.
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  23. Terrell Ward Bynum (2014). On the Possibility of Quantum Informational Structural Realism. Minds and Machines 24 (1):123-139.
    In The Philosophy of Information, Luciano Floridi presents an ontological theory of Being qua Being, which he calls “Informational Structural Realism”, a theory which applies, he says, to every possible world. He identifies primordial information (“dedomena”) as the foundation of any structure in any possible world. The present essay examines Floridi’s defense of that theory, as well as his refutation of “Digital Ontology” (which some people might confuse with his own). Then, using Floridi’s ontology as a starting point, the present (...)
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  24. Laureano Cabanero & C. G. Small (2009). Intentionality and Computationalism: A Diagonal Argument. Mind and Matter 7 (1):81-90.
    Computationalism is the claim that all possible thoughts are computations, i.e. executions of algorithms. The aim of the paper is to show that if intentionality is semantically clear, in a way defined in the paper, then computationalism must be false. Using a convenient version of the phenomenological relation of intentionality and a diagonalization device inspired by Thomson's theorem of 1962, we show there exists a thought that cannot be a computation.
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  25. Liming Cai, Jianer Chen, Rodney G. Downey & Michael R. Fellows (1997). On the Parameterized Complexity of Short Computation and Factorization. Archive for Mathematical Logic 36 (4-5):321-337.
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  26. C. S. Calude & J. L. Casti (1998). Introduction to Unconventional Models of Computation. Complexity 4 (1):13-13.
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  27. Wesley Calvert (forthcoming). On Three Notions of Effective Computation Over R. Logic Journal of the Igpl.
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  28. Paco Calvo & John Symons, Radical Embodiment and Morphological Computation: Against the Autonomy of (Some) Special Sciences.
    An asymmetry between the demands at the computational and algorithmic levels of description furnishes the illusion that the abstract profile at the computational level can be multiply realized, and that something is actually being shared at the algorithmic one. A disembodied rendering of the situation lays the stress upon the different ways in which an algorithm can be implemented. However, from an embodied approach, things look rather different. The relevant pairing, I shall argue, is not between implementation and algorithm, but (...)
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  29. John L. Casti (1997). Computing the Uncomputable. Complexity 2 (3):7-12.
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  30. Ronald L. Chrisley, (Ronc@Cogs.Susx.Ac. Uk).
    imply that computational states are not "real", and cannot, for example, provide a foundation for the cognitive sciences. In particular, Putnam has argued that every ordinary open physical system realizes every abstract finite automaton, implying that the fact that a particular computational characterization applies to a physical system does not tell one anything about the nature of that system. Putnam's argument is scrutinized, and found inadequate because, among other things, it employs a notion of causation that is too weak. I (...)
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  31. Ronald L. Chrisley (1992). Taking Embodiment Seriously Non-Conceptual Content and Computation. School of Cognitive and Computing Sciences, University of Sussex.
  32. D. S. Clarke Jr (1988). Consciousness and the Computational Mind. Review of Metaphysics 42 (1):147-149.
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  33. Carol Cleland (forthcoming). Effective Procedures and Causal Processes. Minds and Machines.
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  34. Jonathan Cohen (2012). Computation and the Ambiguity of Perception. In Gary Hatfield & Sarah Allred (eds.), Visual Experience: Sensation, Cognition, and Constancy. Oup Oxford. 160.
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  35. William P. Coleman (forthcoming). Models of Computational Processes. Journal of Symbolic Logic.(Presented at the Spring Meeting 1989 of the Association for Symbolic Logic. Manuscript in Progress.).
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  36. S. Barry Cooper (2013). What Makes A Computation Unconventional? In Gordana Dodig-Crnkovic Raffaela Giovagnoli (ed.), Computing Nature. 255--269.
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  37. B. Jack Copeland, The Modern History of Computing. Stanford Encyclopedia of Philosophy.
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  38. Paolo Cotogno (forthcoming). Buttresses of the Turing Barrier. Acta Analytica:1-8.
    The ‘Turing barrier’ is an evocative image for 0′, the degree of the unsolvability of the halting problem for Turing machines—equivalently, of the undecidability of Peano Arithmetic . The ‘barrier’ metaphor conveys the idea that effective computability is impaired by restrictions that could be removed by infinite methods. Assuming that the undecidability of PA is essentially depending on the finite nature of its computational means, decidability would be restored by the ω-rule. Hypercomputation, the hypothetical realization of infinitary machines through relativistic (...)
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  39. Paolo Cotogno (2003). Hypercomputation and the Physical Church-Turing Thesis. British Journal for the Philosophy of Science 54 (2):181-223.
    A version of the Church-Turing Thesis states that every effectively realizable physical system can be defined by Turing Machines (‘Thesis P’); in this formulation the Thesis appears an empirical, more than a logico-mathematical, proposition. We review the main approaches to computation beyond Turing definability (‘hypercomputation’): supertask, non-well-founded, analog, quantum, and retrocausal computation. These models depend on infinite computation, explicitly or implicitly, and appear physically implausible; moreover, even if infinite computation were realizable, the Halting Problem would not be affected. Therefore, Thesis (...)
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  40. Ron Cottam, Willy Ranson & Roger Vounckx (2013). A Framework for Computing Like Nature. In Gordana Dodig-Crnkovic Raffaela Giovagnoli (ed.), Computing Nature. 23--60.
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  41. E. B. Dahlin & R. N. Linebarger (1965). Digital Simulation Applied to Paper Machine Dryer Studies. In Karl W. Linsenmann (ed.), Proceedings. St. Louis, Lutheran Academy for Scholarship.
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  42. Melissa Dark, Nathan Harter, Gram Ludlow & Courtney Falk (2006). Ethical Attributes in Computing and Computing Education: An Exploratory Study. Journal of Information, Communication and Ethics in Society 4 (2):67-75.
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  43. Marc Davio, Jean-Pierre Deschamps & André Thayse (1983). Digital Systems, with Algorithm Implementation.
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  44. Liesbeth De Mol & Giuseppe Primiero (2014). Facing Computing as Technique: Towards a History and Philosophy of Computing. Philosophy and Technology 27 (3):321-326.
    We present the methodological principles underlying the scientific activities of the DHST Commission on the History and Philosophy of Computing. This volume collects refereed selected papers from the First International Conference organized by the Commission.
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  45. Giorgio de Santillana (1994). Continuous Computation and the Emergence of the Discrete. In Karl H. Pribram (ed.), Origins: Brain and Self-Organization. Lawrence Erlbaum.
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  46. Walter H. Dean, What Algorithms Could Not Be.
    This dissertation addresses a variety of foundational issues pertaining to the notion of algorithm employed in mathematics and computer science. In these settings, an algorithm is taken to be an effective mathematical procedure for solving a previously stated mathematical problem. Procedures of this sort comprise the notional subject matter of the subfield of computer science known as algorithmic analysis. In this context, algorithms are referred to via proper names of which computational properties are directly predicated )). Moreover, many formal results (...)
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  47. Michael Detlefsen (1995). The Mechanization of Reason. Philosophia Mathematica 3 (1).
    Introduction to a special issue of Philosophia Mathematica on the mechanization of reasoning. Authors include: M. Detlefsen, D. Mundici, S. Shanker, S. Shapiro, W. Sieg and C. Wright.
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  48. Joris Van Deun & Ronald Cools (2006). Methods and Software for Computing Mathematical Functions-A Matlab Implementation of an Algorithm for Computing Integrals of Products of Bessel Functions. In O. Stock & M. Schaerf (eds.), Lecture Notes in Computer Science. Springer-Verlag. 284-295.
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  49. Vincent J. Digricoli (1986). Mind and Computer. Thought: A Journal of Philosophy 61 (4):442-451.
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  50. Gordana Dodig Crnkovic & Raffaela Giovagnoli (2013). Computing Nature. Springer.
    This book is about nature considered as the totality of physical existence, the universe, and our present day attempts to understand it.
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