Results for 'Siam J. Comput'

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  1. Randomness and Recursive Enumerability.Siam J. Comput - unknown
    One recursively enumerable real α dominates another one β if there are nondecreasing recursive sequences of rational numbers (a[n] : n ∈ ω) approximating α and (b[n] : n ∈ ω) approximating β and a positive constant C such that for all n, C(α − a[n]) ≥ (β − b[n]). See [R. M. Solovay, Draft of a Paper (or Series of Papers) on Chaitin’s Work, manuscript, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, 1974, p. 215] and [G. J. (...)
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  2. Is having your computer compromised a personal assault? The ethics of extended cognition.J. Adam Carter & S. Orestis Palermos - 2016 - Journal of the American Philosophical Association 2 (4):542-560.
    Philosophy of mind and cognitive science have recently become increasingly receptive to the hypothesis of extended cognition, according to which external artifacts such as our laptops and smartphones can—under appropriate circumstances—feature as material realizers of a person's cognitive processes. We argue that, to the extent that the hypothesis of extended cognition is correct, our legal and ethical theorizing and practice must be updated by broadening our conception of personal assault so as to include intentional harm toward gadgets that have been (...)
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  3.  42
    Shafi Goldwasser, Silvio Micali, and Charles Rackoff. The knowledge complexity of interactive proof systems. SIAM journal on computing, vol. 18 , pp. 186–208. - Oded Goldreich, Silvio Micali, and Avi Wigderson. Proofs that release minimum knowledge. Mathematical foundations of computer science 1986, Proceedings of the 12th symposium, Bratislava, Czechoslovakia, August 25–29, 1986, edited by J. Gruska, B. Rovan, and J. Wiedermann, Lecture notes in computer science, vol. 233, Springer-Verlag, Berlin, Heidelberg, New York, etc., 1986, pp. 639–650. - Oded Goldreich. Randomness, interactive proofs, and zero-knowledge—a survey. The universal Turing machine, A half-century survey, edited by Rolf Herken, Kammerer & Unverzagt, Hamburg and Berlin, and Oxford University Press, Oxford and New York, 1988, pp. 377–405. [REVIEW]Lance Fortnow - 1991 - Journal of Symbolic Logic 56 (3):1092-1094.
  4. From cognitivism to autopoiesis: towards a computational framework for the embodied mind.Micah Allen & Karl J. Friston - 2018 - Synthese 195 (6):2459-2482.
    Predictive processing approaches to the mind are increasingly popular in the cognitive sciences. This surge of interest is accompanied by a proliferation of philosophical arguments, which seek to either extend or oppose various aspects of the emerging framework. In particular, the question of how to position predictive processing with respect to enactive and embodied cognition has become a topic of intense debate. While these arguments are certainly of valuable scientific and philosophical merit, they risk underestimating the variety of approaches gathered (...)
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  5.  57
    Connectionist Models and Their Properties.J. A. Feldman & D. H. Ballard - 1982 - Cognitive Science 6 (3):205-254.
    Much of the progress in the fields constituting cognitive science has been based upon the use of explicit information processing models, almost exclusively patterned after conventional serial computers. An extension of these ideas to massively parallel, connectionist models appears to offer a number of advantages. After a preliminary discussion, this paper introduces a general connectionist model and considers how it might be used in cognitive science. Among the issues addressed are: stability and noise‐sensitivity, distributed decision‐making, time and sequence problems, and (...)
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  6.  18
    Computable structures of rank.J. F. Knight & J. Millar - 2010 - Journal of Mathematical Logic 10 (1):31-43.
    For countable structure, "Scott rank" provides a measure of internal, model-theoretic complexity. For a computable structure, the Scott rank is at most [Formula: see text]. There are familiar examples of computable structures of various computable ranks, and there is an old example of rank [Formula: see text]. In the present paper, we show that there is a computable structure of Scott rank [Formula: see text]. We give two different constructions. The first starts with an arithmetical example due to Makkai, and (...)
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  7. The computational and the representational language-of-thought hypotheses.David J. Chalmers - 2023 - Behavioral and Brain Sciences 46:e269.
    There are two versions of the language-of-thought hypothesis (LOT): Representational LOT (roughly, structured representation), introduced by Ockham, and computational LOT (roughly, symbolic computation) introduced by Fodor. Like many others, I oppose the latter but not the former. Quilty-Dunn et al. defend representational LOT, but they do not defend the strong computational LOT thesis central to the classical-connectionist debate.
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  8.  7
    Computable structures of rank omega (ck)(1).J. F. Knight & J. Millar - 2010 - Journal of Mathematical Logic 10 (1):31-43.
    For countable structure, "Scott rank" provides a measure of internal, model-theoretic complexity. For a computable structure, the Scott rank is at most [Formula: see text]. There are familiar examples of computable structures of various computable ranks, and there is an old example of rank [Formula: see text]. In the present paper, we show that there is a computable structure of Scott rank [Formula: see text]. We give two different constructions. The first starts with an arithmetical example due to Makkai, and (...)
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  9.  44
    Computability of Recursive Functions.J. C. Shepherdson & H. E. Sturgis - 1967 - Journal of Symbolic Logic 32 (1):122-123.
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  10.  16
    Abstraction and Representation in Living Organisms: When Does a Biological System Compute?J. Young, Susan Stepney, Viv Kendon & Dominic Horsman - 2017 - In Gordana Dodig-Crnkovic & Raffaela Giovagnoli (eds.), Representation of Reality: Humans, Other Living Organism and Intelligent Machines. Heidelberg: Springer.
    Even the simplest known living organisms are complex chemical processing systems. But how sophisticated is the behaviour that arises from this? We present a framework in which even bacteria can be identified as capable of representing information in arbitrary signal molecules, to facilitate altering their behaviour to optimise their food supplies, for example. Known asion/Representation theory, this framework makes precise the relationship between physical systems and abstract concepts. Originally developed to answer the question of when a physical system is computing, (...)
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  11. Computing in the nick of time.J. Brendan Ritchie & Colin Klein - 2023 - Ratio 36 (3):169-179.
    The medium‐independence of computational descriptions has shaped common conceptions of computational explanation. So long as our goal is to explain how a system successfully carries out its computations, then we only need to describe the abstract series of operations that achieve the desired input–output mapping, however they may be implemented. It is argued that this abstract conception of computational explanation cannot be applied to so‐called real‐time computing systems, in which meeting temporal deadlines imposed by the systems with which a device (...)
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  12. The Ethics of Extended Cognition: Is Having your Computer Compromised a Personal Assault?J. Adam Carter & S. Orestis Palermos - forthcoming - Journal of the American Philosophical Association.
    Philosophy of mind and cognitive science (e.g., Clark and Chalmers 1998; Clark 2010; Palermos 2014) have recently become increasingly receptive tothe hypothesis of extended cognition, according to which external artifacts such as our laptops and smartphones can—under appropriate circumstances—feature as material realisers of a person’s cognitive processes. We argue that, to the extent that the hypothesis of extended cognition is correct, our legal and ethical theorising and practice must be updated, by broadening our conception of personal assault so as to (...)
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  13.  10
    Artificial evil and the foundation of computer ethics.J. W. Sanders & Luciano Floridi - 2001 - Ethics and Information Technology 3 (1):55-66.
    Moral reasoning traditionally distinguishes two types of evil:moral and natural. The standard view is that ME is the product of human agency and so includes phenomena such as war, torture and psychological cruelty; that NE is the product of nonhuman agency, and so includes natural disasters such as earthquakes, floods, disease and famine; and finally, that more complex cases are appropriately analysed as a combination of ME and NE. Recently, as a result of developments in autonomousagents in cyberspace, a new (...)
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  14.  44
    The uncertain reasoner's companion: a mathematical perspective.J. B. Paris - 1994 - New York: Cambridge University Press.
    Reasoning under uncertainty, that is, making judgements with only partial knowledge, is a major theme in artificial intelligence. Professor Paris provides here an introduction to the mathematical foundations of the subject. It is suited for readers with some knowledge of undergraduate mathematics but is otherwise self-contained, collecting together the key results on the subject, and formalising within a unified framework the main contemporary approaches and assumptions. The author has concentrated on giving clear mathematical formulations, analyses, justifications and consequences of the (...)
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  15. Syntactic semantics: Foundations of computational natural language understanding.William J. Rapaport - 1988 - In James H. Fetzer (ed.), Aspects of AI. Kluwer Academic Publishers.
    This essay considers what it means to understand natural language and whether a computer running an artificial-intelligence program designed to understand natural language does in fact do so. It is argued that a certain kind of semantics is needed to understand natural language, that this kind of semantics is mere symbol manipulation (i.e., syntax), and that, hence, it is available to AI systems. Recent arguments by Searle and Dretske to the effect that computers cannot understand natural language are discussed, and (...)
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  16. Philosophy of Computer Science.William J. Rapaport - 2005 - Teaching Philosophy 28 (4):319-341.
    There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments.
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  17.  37
    From Generative Models to Generative Passages: A Computational Approach to (Neuro) Phenomenology.Maxwell J. D. Ramstead, Anil K. Seth, Casper Hesp, Lars Sandved-Smith, Jonas Mago, Michael Lifshitz, Giuseppe Pagnoni, Ryan Smith, Guillaume Dumas, Antoine Lutz, Karl Friston & Axel Constant - 2022 - Review of Philosophy and Psychology 13 (4):829-857.
    This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. Our approach can be described as _computational phenomenology_ because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates (...)
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  18. Nonlinearity, liveliness and the relation of man-computer systems.J. Rajchl - 1986 - Filosoficky Casopis 34 (3):506-508.
  19. On implementing a computation.David J. Chalmers - 1994 - Minds and Machines 4 (4):391-402.
    To clarify the notion of computation and its role in cognitive science, we need an account of implementation, the nexus between abstract computations and physical systems. I provide such an account, based on the idea that a physical system implements a computation if the causal structure of the system mirrors the formal structure of the computation. The account is developed for the class of combinatorial-state automata, but is sufficiently general to cover all other discrete computational formalisms. The implementation relation is (...)
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  20.  19
    The Computer Comes of Age: The People, the Hardware, and the Software by Rene Moreau; J. Howlett; Engines of the Mind: A History of the Computer by Joel Shurkin.J. Bolter - 1985 - Isis 76:113-115.
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  21.  23
    Computable structures and the hyperarithmetical hierarchy.C. J. Ash - 2000 - New York: Elsevier. Edited by J. Knight.
    This book describes a program of research in computable structure theory. The goal is to find definability conditions corresponding to bounds on complexity which persist under isomorphism. The results apply to familiar kinds of structures (groups, fields, vector spaces, linear orderings Boolean algebras, Abelian p-groups, models of arithmetic). There are many interesting results already, but there are also many natural questions still to be answered. The book is self-contained in that it includes necessary background material from recursion theory (ordinal notations, (...)
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  22. A survey of abstract algebraic logic.J. M. Font, R. Jansana & D. Pigozzi - 2003 - Studia Logica 74 (1-2):13 - 97.
  23.  62
    Foundations of Logic Programming.J. W. Lloyd - 1987 - Journal of Symbolic Logic 52 (1):288-289.
  24. Semiotic Systems, Computers, and the Mind: How Cognition Could Be Computing.William J. Rapaport - 2012 - International Journal of Signs and Semiotic Systems 2 (1):32-71.
    In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers are (...)
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  25. Turing's Man: Western Culture in the Computer Age.J. D. Bolter - 1985 - Australasian Journal of Philosophy 63:520.
     
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  26.  24
    On the Definition of Computable Function of a Real Variable.J. C. Shepherdson - 1976 - Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 22 (1):391-402.
  27.  86
    What is a Computer? A Survey.William J. Rapaport - 2018 - Minds and Machines 28 (3):385-426.
    A critical survey of some attempts to define ‘computer’, beginning with some informal ones, then critically evaluating those of three philosophers, and concluding with an examination of whether the brain and the universe are computers.
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  28.  10
    On the Definition of Computable Function of a Real Variable.J. C. Shepherdson - 1976 - Mathematical Logic Quarterly 22 (1):391-402.
  29. Bacteria are small but not stupid: cognition, natural genetic engineering and socio-bacteriology.J. A. Shapiro - 2007 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 38 (4):807-819.
    Forty years’ experience as a bacterial geneticist has taught me that bacteria possess many cognitive, computational and evolutionary capabilities unimaginable in the first six decades of the twentieth century. Analysis of cellular processes such as metabolism, regulation of protein synthesis, and DNA repair established that bacteria continually monitor their external and internal environments and compute functional outputs based on information provided by their sensory apparatus. Studies of genetic recombination, lysogeny, antibiotic resistance and my own work on transposable elements revealed multiple (...)
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  30.  19
    Computable explanations.J. V. Howard - 1975 - Mathematical Logic Quarterly 21 (1):215-224.
  31. How minds can be computational systems.William J. Rapaport - 1998 - Journal of Experimental and Theoretical Artificial Intelligence 10 (4):403-419.
    The proper treatment of computationalism, as the thesis that cognition is computable, is presented and defended. Some arguments of James H. Fetzer against computationalism are examined and found wanting, and his positive theory of minds as semiotic systems is shown to be consistent with computationalism. An objection is raised to an argument of Selmer Bringsjord against one strand of computationalism, namely, that Turing-Test± passing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will inevitably (...)
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  32.  28
    Computer-Assisted Decision Making in Medicine.J. C. Kunz, E. H. Shortliffe, B. G. Buchanan & E. A. Feigenbaum - 1984 - Journal of Medicine and Philosophy 9 (2):135-160.
    This article reviews the strengths and limitations of five major paradigms of medical computer-assisted decision making (CADM): (1) clinical algorithms, (2) statistical analysis of collections of patient data, (3) mathematical models of physical processes, (4) decision analysis, and (5) symbolic reasoning or artificial intelligence (Al). No one technique is best for all applications, and there is recent promising work which combines two or more established techniques. We emphasize both the inherent power of symbolic reasoning and the promise of artificial intelligence (...)
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  33. Doubt And Certainty In Science.J. Z. Young - 1951 - Clarendon Press.
  34. Syntax, Semantics, and Computer Programs.William J. Rapaport - 2020 - Philosophy and Technology 33 (2):309-321.
    Turner argues that computer programs must have purposes, that implementation is not a kind of semantics, and that computers might need to understand what they do. I respectfully disagree: Computer programs need not have purposes, implementation is a kind of semantic interpretation, and neither human computers nor computing machines need to understand what they do.
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  35.  23
    Towards a Mathematical Science of Computation.J. Mccarthy, Cicely M. Popplewell, John Mccarthy & Wayne A. Kalenich - 1962 - Journal of Symbolic Logic 36 (2):346-347.
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  36.  22
    Nondeterministic Ω‐Computations and the Analytical Hierarchy.J. Castro & F. Cucker - 1989 - Mathematical Logic Quarterly 35 (4):333-342.
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  37.  31
    Nondeterministic Ω-Computations and the Analytical Hierarchy.J. Castro & F. Cucker - 1989 - Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 35 (4):333-342.
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  38. Subsymbolic computation and the chinese room.David J. Chalmers - 1992 - In J. Dinsmore (ed.), The Symbolic and Connectionist Paradigms: Closing the Gap. Lawrence Erlbaum. pp. 25--48.
    More than a decade ago, philosopher John Searle started a long-running controversy with his paper “Minds, Brains, and Programs” (Searle, 1980a), an attack on the ambitious claims of artificial intelligence (AI). With his now famous _Chinese Room_ argument, Searle claimed to show that despite the best efforts of AI researchers, a computer could never recreate such vital properties of human mentality as intentionality, subjectivity, and understanding. The AI research program is based on the underlying assumption that all important aspects of (...)
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  39.  85
    Partiality and its dual.J. Michael Dunn - 2000 - Studia Logica 66 (1):5-40.
    This paper explores allowing truth value assignments to be undetermined or "partial" and overdetermined or "inconsistent", thus returning to an investigation of the four-valued semantics that I initiated in the sixties. I examine some natural consequence relations and show how they are related to existing logics, including ukasiewicz's three-valued logic, Kleene's three-valued logic, Anderson and Belnap's relevant entailments, Priest's "Logic of Paradox", and the first-degree fragment of the Dunn-McCall system "R-mingle". None of these systems have nested implications, and I investigate (...)
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  40. The imagery debate revisited: A computational perspective.J. I. Glasgow - 1993 - Computational Intelligence 9:310-33.
     
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  41.  33
    Multimo dal Logics of Products of Topologies.J. Van Benthem, G. Bezhanishvili, B. Ten Cate & D. Sarenac - 2006 - Studia Logica 84 (3):369 - 392.
    We introduce the horizontal and vertical topologies on the product of topological spaces, and study their relationship with the standard product topology. We show that the modal logic of products of topological spaces with horizontal and vertical topologies is the fusion ${\bf S4}\oplus {\bf S4}$ . We axiomatize the modal logic of products of spaces with horizontal, vertical, and standard product topologies. We prove that both of these logics are complete for the product of rational numbers ${\Bbb Q}\times {\Bbb Q}$ (...)
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  42. Understanding understanding: Syntactic semantics and computational cognition.William J. Rapaport - 1995 - Philosophical Perspectives 9:49-88.
    John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? Yes: Everything (...)
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  43. Computers Are Syntax All the Way Down: Reply to Bozşahin.William J. Rapaport - 2019 - Minds and Machines 29 (2):227-237.
    A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.
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  44. Computer knows best? The need for value-flexibility in medical AI.Rosalind J. McDougall - 2019 - Journal of Medical Ethics 45 (3):156-160.
    Artificial intelligence is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM’s Watson for Oncology. I argue that use of this type of system creates (...)
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  45.  17
    Cooperation.J. McKenzie Alexander - 2008 - In Sahorta Sarkar & Anya Plutynski (eds.), Companion to the Philosophy of Biology. Blackwell. pp. 415-430.
    This chapter contains section titled: Kin Selection Reciprocity Group Selection Coercion Mutualism Byproduct Mutualism Local Interactions References.
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  46.  82
    The complexity of marketplace logic.J. Almog - 1997 - Linguistics and Philosophy 20 (5):549-569.
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  47.  24
    Computable Embeddings and Strongly Minimal Theories.J. Chisholm, J. F. Knight & S. Miller - 2007 - Journal of Symbolic Logic 72 (3):1031 - 1040.
    Here we prove that if T and T′ are strongly minimal theories, where T′ satisfies a certain property related to triviality and T does not, and T′ is model complete, then there is no computable embedding of Mod(T) into Mod(T′). Using this, we answer a question from [4], showing that there is no computable embedding of VS into ZS, where VS is the class of infinite vector spaces over Q, and ZS is the class of models of Th(Z, S). Similarly, (...)
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  48.  19
    The Essential Turing.B. J. Copeland (ed.) - 2004 - Oxford University Press UK.
    Lectures, scientific papers, top secret wartime material, correspondence, and broadcasts are introduced and set in context by Jack Copeland, Director of the Turing Archive for the History of Computing."--Jacket.
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  49. Bacteria are small but not stupid: Cognition, natural genetic engineering and socio-bacteriology.J. A. Shapiro - 2007 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 38 (4):807-819.
    Forty years’ experience as a bacterial geneticist has taught me that bacteria possess many cognitive, computational and evolutionary capabilities unimaginable in the first six decades of the twentieth century. Analysis of cellular processes such as metabolism, regulation of protein synthesis, and DNA repair established that bacteria continually monitor their external and internal environments and compute functional outputs based on information provided by their sensory apparatus. Studies of genetic recombination, lysogeny, antibiotic resistance and my own work on transposable elements revealed multiple (...)
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  50.  11
    Intellectual autonomy, epistemic dependence and cognitive enhancement.J. Adam Carter - 2020 - Synthese 197 (7):2937-2961.
    Intellectual autonomy has long been identified as an epistemic virtue, one that has been championed influentially by (among others) Kant, Hume and Emerson. Manifesting intellectual autonomy, at least, in a virtuous way, does not require that we form our beliefs in cognitive isolation. Rather, as Roberts and Wood (Intellectual virtues: an essay in regulative epistemology, OUP Oxford, Oxford, pp. 259–260, 2007) note, intellectually virtuous autonomy involves reliance and outsourcing (e.g., on other individuals, technology, medicine, etc.) to an appropriate extent, while (...)
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