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  1. Philosophy.Robert A. Wilson - 1999 - In Robert A. Wilson & Frank C. Keil (eds.), MIT Encyclopedia of the Cognitive Sciences. Cambridge, MA, USA:
    This is an introduction to the 80 articles on philosophy in MITECS.
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  2. Autômatos, Androides e Bergson ou A percepção e a Extensão em seres artificiais da Ficção: Um olhar Bergsoniano.Sandro Rinaldi Feliciano - 2016 - Dissertation, Universidade Federal Do ABC
    Androides são "autômatos com forma humana" . Enquanto robôs são "aparelhos automáticos capazes de manipular objetos ou executar operações segundo um programa". Assim podemos dizer que um androide pode ser considerado um robô, mas nem todo robô é um androide. Devido à diversidade de gêneros, foi criado o termo ginóide, separando-se assim os androides de aparência masculina (andros) da feminina (ginos). A propagação destes se deu à ficção cientifica, em livros de Isaac Asimov, em seriados para televisão como Jornada nas (...)
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  3. Physical Computation: A Mechanistic Account, by Gualtiero Piccinini: Oxford: Oxford University Press, 2015, Pp. Ix + 343, £35. [REVIEW]Nir Fresco - 2017 - Australasian Journal of Philosophy 95 (3):625-626.
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  4. Physical Computation and Cognitive Science, by Nir Fresco: Heidelberg: Springer, 2014, Pp. Xxii + 229, 99,99€. [REVIEW]Gordana Dodig-Crnkovic - 2016 - Australasian Journal of Philosophy 94 (2):396-399.
    This is review of the book "Physical Computation and Cognitive Science" by Nir Fresco: http://www.springer.com/la/book/9783642413742.
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  5. Using Computational Models to Discover and Understand Mechanisms.William Bechtel - 2016 - Studies in History and Philosophy of Science Part A 56:113-121.
  6. Emergence, Computation and the Freedom Degree Loss Information Principle in Complex Systems.Ignazio Licata & Gianfranco Minati - 2017 - Foundations of Science 22 (4):863-881.
    We consider processes of emergence within the conceptual framework of the Information Loss principle and the concepts of systems conserving information; systems compressing information; and systems amplifying information. We deal with the supposed incompatibility between emergence and computability tout-court. We distinguish between computational emergence, when computation acquires properties, and emergent computation, when computation emerges as a property. The focus is on emergence processes occurring within computational processes. Violations of Turing-computability such as non-explicitness and incompleteness are intended to represent partially the (...)
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  7. Social Autonomy and Heteronomy in the Age of ICT: The Digital Pharmakon and the (Dis)Empowerment of the General Intellect.Pieter Lemmens - 2017 - Foundations of Science 22 (2):287-296.
    ‘The art of living with ICTs ’ today not only means finding new ways to cope, interact and create new lifestyles on the basis of the new digital technologies individually, as ‘consumer-citizens’. It also means inventing new modes of living, producing and, not in the least place, struggling collectively, as workers and producers. As the so-called digital revolution unfolds in the context of a neoliberal cognitive and consumerist capitalism, its ‘innovations’ are predominantly employed to modulate and control both production processes (...)
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  8. 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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  9. Hypercomputation and the Physical Church‐Turing Thesis.Paolo Cotogno - 2003 - 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 simulated by Turing Machines (‘Thesis P’). In this formulation the Thesis appears to be an empirical hypothesis, subject to physical falsification. We review the main approaches to computation beyond Turing definability (‘hypercomputation’): supertask, non-well-founded, analog, quantum, and retrocausal computation. The conclusions are that these models reduce to supertasks, i.e. infinite computation, and that even supertasks are no solution for recursive incomputability. This yields that the realization (...)
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  10. Mental Algorithms: Are Minds Computational Systems?James H. Fetzer - 1994 - Pragmatics and Cognition 2 (1):1-29.
    The idea that human thought requires the execution of mental algorithms provides a foundation for research programs in cognitive science, which are largely based upon the computational conception of language and mentality. Consideration is given to recent work by Penrose, Searle, and Cleland, who supply various grounds for disputing computationalism. These grounds in turn qualify as reasons for preferring a non-computational, semiotic approach, which can account for them as predictable manifestations of a more adquate conception. Thinking does not ordinarily require (...)
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  11. Searle's Mind: Physical, Irreducible, Subjective, and Non-Computational.Amir Horowitz - 1994 - Pragmatics and Cognition 2 (1):207-220.
  12. Computational Tractability and Conceptual Coherence: Why Do Computer Scientists Believe That P≠NP?Paul Thagard - 1993 - Canadian Journal of Philosophy 23 (3):349-363.
    According to Church’s thesis, we can identify the intuitive concept of effective computability with such well-defined mathematical concepts as Turing computability and partial recursiveness. The almost universal acceptance of Church’s thesis among logicians and computer scientists is puzzling from some epistemological perspectives, since no formal proof is possible of a thesis that involves an informal concept such as effectiveness. Elliott Mendelson has recently argued, however, that equivalencies between intuitive notions and precise notions need not always be considered unprovable theses, and (...)
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  13. Consciousness and the Computational Mind. [REVIEW]D. S. Clarke Jr - 1988 - Review of Metaphysics 42 (1):147-149.
    The term 'consciousness' has not been consistently used in the history of philosophy and psychology. It has been taken to stand for the mental activity in which all of us are engaged during our waking lives, whether absorbed in the solving of a task or in calm moments of contemplation. It has also been allied with the term 'introspection' to stand for a self-monitoring activity, one in which we are not simply engaged, but in which we aware of the succession (...)
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  14. A Philosophy of Computing? - The Case of Sociology and Computing.H. Robinson - 1993 - Journal of Intelligent Systems 3 (2-4):189-216.
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  15. Computational Models of Consciousness: An Evaluation.Ron Sun - 1999 - Journal of Intelligent Systems 9 (5-6):507-568.
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  16. Design and Implementation of SeTiA: Secure Multi Auction System II: Architecture and Implementation Issues.V. S. Borkar, M. S. Dave & R. K. Shyamasundar - 2005 - Journal of Intelligent Systems 14 (1):69-93.
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  17. Computing is at Best a Special Kind of Thinking.James H. Fetzer - 2000 - The Proceedings of the Twentieth World Congress of Philosophy 9:103-113.
    When computing is defined as the causal implementation of algorithms and algorithms are defined as effective decision procedures, human thought is mental computation only if it is governed by mental algorithms. An examination of ordinary thinking, however, suggests that most human thought processes are non-algorithmic. Digital machines, moreover, are mark-manipulating or string-processing systems whose marks or strings do not stand for anything for those systems, while minds are semiotic systems for which signs stand for other things for those systems. Computing, (...)
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  18. Informational Macrodynamics for Cognitive Information Modeling and Computation.Vladimir S. Lerner - 2001 - Journal of Intelligent Systems 11 (6):409-470.
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  19. Parallel Implementation of Backpropagation Algorithm.R. Szabo & M. Steinmetz - 1996 - Journal of Intelligent Systems 6 (3-4):261-278.
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  20. The Computational Notion of Life.Ciaus Emmeche - 1994 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 9 (2):1-30.
    The present paper discusses a topic often neglected by contemporary philosophy of biology: The relation between metaphorical notions of living organisms as information processing systems, the attempts to model such systems by computational means, and the idea that life itself is a computational phenomenon. This question has ramifications in theoretical biology and thedefinition of Iife, in theoretical computer science and the concept of computation, and in semiotics, and the concept of the interpreter. It is argued, that the theory of autopoietic (...)
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  21. Computation and Causation.Richard Scheines - 2002 - Metaphilosophy 33 (1‐2):158-180.
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  22. Mediation and Metaxý: The Interval Between Analog Animality and Digital Humanity.Thomas Sutherland - unknown
    This article examines Plotinus’ conception of metaxý – the human as interval between animals and gods – and its resonances in the work of Jacques Lacan, who implicitly retains and reconfigures the notion of the human being as a mediator. Lacan replicates this ancient narrative, but does so within the context of a cyberneticism that replaces gods and angels with symbolic computation. Humanity, according to such a conception, is tacitly regarded not only as a mediator, but as that which is (...)
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  23. Gualtiero Piccinini: Physical Computation: A Mechanistic Account: Oxford University Press, Oxford, 2015, Ix + 313, £35.00, ISBN 9780199658855.Matteo Colombo - 2016 - Minds and Machines 26 (3):307-312.
  24. The Importance of Learning History and Philosophy of Computing.Colin Price - unknown
    Computers have invaded our offices, our homes, cars and coffee-pots; they have become ubiquitous. However, the advance of computing technologies is associated with an increasing lack of “visibility” of the underlying software and hardware technologies. While we use and accept the computer, we neither know its history nor functionality. In this paper, we argue that this is not a healthy situation. Also, recruitment onto UK Computing degree courses is steadily falling; these courses are appearing less attractive to school-leavers. This may (...)
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  25. 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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  26. Computation in Non-Classical Foundations?Toby Meadows & Zach Weber - 2016 - Philosophers' Imprint 16.
    The Church-Turing Thesis is widely regarded as true, because of evidence that there is only one genuine notion of computation. By contrast, there are nowadays many different formal logics, and different corresponding foundational frameworks. Which ones can deliver a theory of computability? This question sets up a difficult challenge: the meanings of basic mathematical terms are not stable across frameworks. While it is easy to compare what different frameworks say, it is not so easy to compare what they mean. We (...)
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  27. Models of Neural Computation: An Examination of David Chalmers’ Causal Theory of the Mind.Dinyar Mistry - unknown
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  28. From Aristotle to John Searle and Back Again: Formal Causes, Teleology, and Computation in Nature.Edward Feser - 2016 - Nova et Vetera 14 (2):459-494.
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  29. Inleiding: 'History of Computing'. Geschiedschrijving Over Computers En Computergebruik in Nederland.Adrienne van den Boogaard - 2008 - Studium : Revue D’Histoire des Sciences Et des Universités 1 (2):89.
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  30. What Computations (Still, Still) Can't Do: Jerry Fodor on Computation and Modularity.Robert A. Wilson - 2004 - Canadian Journal of Philosophy 34 (sup1):407-425.
    Fodor's thinking on modularity has been influential throughout a range of the areas studying cognition, chiefly as a prod for positive work on modularity and domain-specificity. In _The Mind Doesn't Work That Way_, Fodor has developed the dark message of _The Modularity of Mind_ regarding the limits to modularity and computational analyses. This paper offers a critical assessment of Fodor's scepticism with an eye to highlighting some broader issues in play, including the nature of computation and the role of recent (...)
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  31. Computation and Consciousness.Tim Maudlin - 1989 - Journal of Philosophy 86 (8):407.
  32. On the Parallel Computation Thesis.Nachum Dershowitz & Evgenia Falkovich-Derzhavetz - 2016 - Logic Journal of the IGPL 24 (3):346-374.
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  33. 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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  34. Effect of Material Stiffness on Hardness: A Computational Study Based on Model Potentials.Gerolf Ziegenhain & Herbert M. Urbassek - 2009 - Philosophical Magazine 89 (26):2225-2238.
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  35. Computational Homogenization of Material Layers with Micromorphic Mesostructure.C. B. Hirschberger, N. Sukumar & P. Steinmann - 2008 - Philosophical Magazine 88 (30-32):3603-3631.
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  36. Numerical Computation of the Director Field in a Twist Wall.Robert Turner - 1975 - Philosophical Magazine 31 (3):719-722.
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  37. Experimental and Computational Creep Characterization of Al–Mg Solid-Solution Alloy Through Instrumented Indentation.Hidenari Takagi, Ming Dao†, Masami Fujiwara‡ & Masahisa Otsuka - 2003 - Philosophical Magazine 83 (35):3959-3976.
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  38. 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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  39. On Using Compressibility to Detect When Slime Mould Completed Computation.Andrew Adamatzky & Jeff Jones - 2016 - Complexity 21 (5):162-175.
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  40. Amorphous Computing.Harold Abelson & Nancy Forbes - 2000 - Complexity 5 (3):22.
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  41. A Plan Recognition Method Using Prefix Computation in Web Access Log Analysis.Ryosuke Kojima & Taisuke Sato - 2014 - Transactions of the Japanese Society for Artificial Intelligence 29 (3):301-310.
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  42. Computational Model for Calculating Curvatures.Haiyang Yu & Seizaburo Niitsuma - 2007 - Transactions of the Japanese Society for Artificial Intelligence 22 (6):595-603.
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  43. Self-Organizing Symbol Acquisition and Motion Generation Based on Dynamics-Based Information Processing System.Masafumi Okada, Daisuke Nakamura & Yoshihiko Nakamura - 2005 - Transactions of the Japanese Society for Artificial Intelligence 20:177-187.
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  44. Brian Oakley and Kenneth Owen. Alvey: Britain's Strategic Computing Initiative. Cambridge, Mass, and London: The MIT Press, 1989. Pp. Xv + 337. ISBN 0-262-15038-7. £24.95. [REVIEW]Geoffrey Tweedale - 1991 - British Journal for the History of Science 24 (1):116-117.
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  45. Landmarks in Digital Computing: A Smithsonian Pictorial History. Peggy A. Kidwell, Paul E. Ceruzzi.Michael S. Mahoney - 1995 - Isis 86 (4):691-692.
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  46. Early Scientific Computing in Britain. Mary Croarken.Michael S. Mahoney - 1992 - Isis 83 (1):167-168.
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  47. The Charles Babbage Institute for the History of Information Processing.Pamela Gullard - 1981 - Isis 72 (2):262-264.
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  48. Computational Modeling of Reading in Semantic Dementia: Comment on Woollams, Lambon Ralph, Plaut, and Patterson.Max Coltheart, Jeremy J. Tree & Steven J. Saunders - 2010 - Psychological Review 117 (1):256-271.
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  49. Validating Computational Models: A Critique of Anderson's Indeterminacy of Representation Claim.Zenon W. Pylyshyn - 1979 - Psychological Review 86 (4):383-394.
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  50. Shorter Contributions: Practical Computation of the Median.E. W. Scripture - 1895 - Psychological Review 2 (4):376-379.
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