Results for ' computation'

954 found
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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. The fortieth annual lecture series 1999-2000.Brain Computations & an Inevitable Conflict - 2000 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 31:199-200.
  3.  10
    Computer Science Logic: 11th International Workshop, CSL'97, Annual Conference of the EACSL, Aarhus, Denmark, August 23-29, 1997, Selected Papers.M. Nielsen, Wolfgang Thomas & European Association for Computer Science Logic - 1998 - Springer Verlag.
    This book constitutes the strictly refereed post-workshop proceedings of the 11th International Workshop on Computer Science Logic, CSL '97, held as the 1997 Annual Conference of the European Association on Computer Science Logic, EACSL, in Aarhus, Denmark, in August 1997. The volume presents 26 revised full papers selected after two rounds of refereeing from initially 92 submissions; also included are four invited papers. The book addresses all current aspects of computer science logics and its applications and thus presents the state (...)
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  4. Computation and Cognition: Toward a Foundation for Cognitive Science.Zenon W. Pylyshyn - 1984 - Cambridge: MIT Press.
    This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking. 1 The Explanatory Vocabulary of Cognition 2 The Explanatory Role of Representations 3 The Relevance of Computation 4 (...)
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  5. Computation, individuation, and the received view on representation.Mark Sprevak - 2010 - Studies in History and Philosophy of Science Part A 41 (3):260-270.
    The ‘received view’ about computation is that all computations must involve representational content. Egan and Piccinini argue against the received view. In this paper, I focus on Egan’s arguments, claiming that they fall short of establishing that computations do not involve representational content. I provide positive arguments explaining why computation has to involve representational content, and how that representational content may be of any type. I also argue that there is no need for computational psychology to be individualistic. (...)
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  6. The varieties of computation: A reply.David Chalmers - 2012 - Journal of Cognitive Science 2012 (3):211-248.
    Computation is central to the foundations of modern cognitive science, but its role is controversial. Questions about computation abound: What is it for a physical system to implement a computation? Is computation sufficient for thought? What is the role of computation in a theory of cognition? What is the relation between different sorts of computational theory, such as connectionism and symbolic computation? In this paper I develop a systematic framework that addresses all of these (...)
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  7. Information processing, computation, and cognition.Gualtiero Piccinini & Andrea Scarantino - 2011 - Journal of Biological Physics 37 (1):1-38.
    Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are (...)
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  8. Analogue Computation and Representation.Corey J. Maley - 2023 - British Journal for the Philosophy of Science 74 (3):739-769.
    Relative to digital computation, analogue computation has been neglected in the philosophical literature. To the extent that attention has been paid to analogue computation, it has been misunderstood. The received view—that analogue computation has to do essentially with continuity—is simply wrong, as shown by careful attention to historical examples of discontinuous, discrete analogue computers. Instead of the received view, I develop an account of analogue computation in terms of a particular type of analogue representation that (...)
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  9.  22
    Hector freytes, Antonio ledda, Giuseppe sergioli and.Roberto Giuntini & Probabilistic Logics in Quantum Computation - 2013 - In Hanne Andersen, Dennis Dieks, Wenceslao J. Gonzalez, Thomas Uebel & Gregory Wheeler, New Challenges to Philosophy of Science. Springer Verlag. pp. 49.
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  10.  55
    Randomness Through Computation: Some Answers, More Questions.Hector Zenil (ed.) - 2011 - World Scientific.
    The book is intended to explain the larger and intuitive concept of randomness by means of computation, particularly through algorithmic complexity and recursion theory. It also includes the transcriptions (by A. German) of two panel discussion on the topics: Is The Universe Random?, held at the University of Vermont in 2007; and What is Computation? (How) Does Nature Compute?, held at the University of Indiana Bloomington in 2008. The book is intended to the general public, undergraduate and graduate (...)
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  11.  7
    Domain Theory, Logic and Computation: Proceedings of the 2nd International Symposium on Domain Theory, Sichuan, China, October 2001.Guo-Qiang Zhang, J. Lawson, Yan-M. Liu & Mao-Kang Luo (eds.) - 2003 - Dordrecht, Netherland: Springer.
    Domains are mathematical structures for information and approximation; they combine order-theoretic, logical, and topological ideas and provide a natural framework for modelling and reasoning about computation. The theory of domains has proved to be a useful tool for programming languages and other areas of computer science, and for applications in mathematics. Included in this proceedings volume are selected papers of original research presented at the 2nd International Symposium on Domain Theory in Chengdu, China. With authors from France, Germany, Great (...)
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  12.  7
    A Model for Proustian Decay.Computer Lars - 2024 - Nordic Journal of Aesthetics 33 (67).
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  13. Section 2. Model Theory.Va Vardanyan, On Provability Resembling Computability, Proving Aa Voronkov & Constructive Logic - 1989 - In Jens Erik Fenstad, Ivan Timofeevich Frolov & Risto Hilpinen, Logic, methodology, and philosophy of science VIII: proceedings of the Eighth International Congress of Logic, Methodology, and Philosophy of Science, Moscow, 1987. New York, NY, U.S.A.: Sole distributors for the U.S.A. and Canada, Elsevier Science.
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  14. Quantum computation and pseudotelepathic games.Jeffrey Bub - 2008 - Philosophy of Science 75 (4):458-472.
    A quantum algorithm succeeds not because the superposition principle allows ‘the computation of all values of a function at once’ via ‘quantum parallelism’, but rather because the structure of a quantum state space allows new sorts of correlations associated with entanglement, with new possibilities for information‐processing transformations between correlations, that are not possible in a classical state space. I illustrate this with an elementary example of a problem for which a quantum algorithm is more efficient than any classical algorithm. (...)
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  15.  43
    Computation and the three worlds.Mario Radovan - 2000 - Minds and Machines 10 (2):255-265.
    Discussions about the achievements and limitations of the various approaches to the development of intelligent systems can have an essential impact on empirically based research, and with that also on the future development of computer technologies. However, such discussions are often based on vague concepts and assumptions. In this context, we claim that the proposed `three-world ontology'' offers the most appropriate conceptual framework in which the basic problems concerned with cognition and computation can be suitably expressed and discussed, although (...)
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  16. 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. (...)
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  17. Physical Computation: How General are Gandy’s Principles for Mechanisms?B. Jack Copeland & Oron Shagrir - 2007 - Minds and Machines 17 (2):217-231.
    What are the limits of physical computation? In his ‘Church’s Thesis and Principles for Mechanisms’, Turing’s student Robin Gandy proved that any machine satisfying four idealised physical ‘principles’ is equivalent to some Turing machine. Gandy’s four principles in effect define a class of computing machines (‘Gandy machines’). Our question is: What is the relationship of this class to the class of all (ideal) physical computing machines? Gandy himself suggests that the relationship is identity. We do not share this view. (...)
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  18.  9
    Contingent Computation: Abstraction, Experience, and Indeterminacy in Computational Aesthetics.M. Beatrice Fazi - 2018 - London: Rowman & Littlefield International.
    In Contingent Computation, M. Beatrice Fazi offers a new theoretical perspective through which we can engage philosophically with computing. The book proves that aesthetics is a viable mode of investigating contemporary computational systems. It does so by advancing an original conception of computational aesthetics that does not just concern art made by or with computers, but rather the modes of being and becoming of computational processes. Contingent Computation mobilises the philosophies of Gilles Deleuze and Alfred North Whitehead in (...)
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  19. Computation and Multiple Realizability.Marcin Miłkowski - 2016 - In Vincent C. Müller, Fundamental Issues of Artificial Intelligence. Cham: Springer. pp. 29-41.
    Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...)
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  20. A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism.John Mark Bishop - 2009 - Cognitive Computation 1 (3):221-233.
    The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components (...)
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  21. Languages, machines, and classical computation.Luis M. Augusto - 2019 - London, UK: College Publications.
    3rd ed, 2021. A circumscription of the classical theory of computation building up from the Chomsky hierarchy. With the usual topics in formal language and automata theory.
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  22. What is morphological computation? On how the body contributes to cognition and control.Vincent Müller & Matej Hoffmann - 2017 - Artificial Life 23 (1):1-24.
    The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “off-loading computation from the brain to the body”, where the body is said to perform “morphological computation”. Our investigation of four characteristic cases of morphological computation in animals and robots shows that the ‘off-loading’ perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We thus distinguish (...)
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  23. Content, computation, and individualism in vision theory.Keith Butler - 1996 - Analysis 56 (3):146-154.
  24.  33
    Social-Computation-Supporting Kinds.David Strohmaier - 2020 - Canadian Journal of Philosophy 50 (7):862-877.
    Social kinds are heterogeneous. As a consequence of this diversity, some authors have sought to identify and analyse different kinds of social kinds. One distinct kind of social kinds, however, has not yet received sufficient attention. I propose that there exists a class of social-computation-supporting kinds, or SCS-kinds for short. These SCS-kinds are united by the function of enabling computations implemented by social groups. Examples of such SCS-kinds arereimbursement form,US dollar bill,chair of the board. I will analyse SCS-kinds, contrast (...)
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  25.  34
    Incremental computation for structured argumentation over dynamic DeLP knowledge bases.Gianvincenzo Alfano, Sergio Greco, Francesco Parisi, Gerardo I. Simari & Guillermo R. Simari - 2021 - Artificial Intelligence 300 (C):103553.
    Structured argumentation systems, and their implementation, represent an important research subject in the area of Knowledge Representation and Reasoning. Structured argumentation advances over abstract argumentation frameworks by providing the internal construction of the arguments that are usually defined by a set of (strict and defeasible) rules. By considering the structure of arguments, it becomes possible to analyze reasons for and against a conclusion, and the warrant status of such a claim in the context of a knowledge base represents the main (...)
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  26. Quantum computation in brain microtubules.Stuart R. Hameroff - 2002 - Physical Review E 65 (6):1869--1896.
    Proposals for quantum computation rely on superposed states implementing multiple computations simultaneously, in parallel, according to quantum linear superposition (e.g., Benioff, 1982; Feynman, 1986; Deutsch, 1985, Deutsch and Josza, 1992). In principle, quantum computation is capable of specific applications beyond the reach of classical computing (e.g., Shor, 1994). A number of technological systems aimed at realizing these proposals have been suggested and are being evaluated as possible substrates for quantum computers (e.g. trapped ions, electron spins, quantum dots, nuclear (...)
     
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  27. The Explanatory Role of Computation in Cognitive Science.Nir Fresco - 2012 - Minds and Machines 22 (4):353-380.
    Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for (...)
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  28.  52
    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 (...)
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  29. Computation and content.Frances Egan - 1995 - Philosophical Review 104 (2):181-203.
  30. 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 (...)
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  31. Natural morphological computation as foundation of learning to learn in humans, other living organisms, and intelligent machines.Gordana Dodig-Crnkovic - 2020 - Philosophies 5 (3):17-32.
    The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...)
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  32. Chaotic neurons and analog computation.Kazuyuki Aihara & Jun Kyung Ryeu - 2001 - Behavioral and Brain Sciences 24 (5):810-811.
    Chaotic dynamics can be related to analog computation. A possibility of electronically implementing the chaos -driven contracting system in the target article is explored with an analog electronic circuit with inevitable noise from the viewpoint of analog computation with chaotic neurons.
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  33.  13
    Logic, Language and Computation.Seiki Akama (ed.) - 1997 - Dordrecht, Netherland: Springer.
    The editors of the Applied Logic Series are happy to present to the reader the fifth volume in the series, a collection of papers on Logic, Language and Computation. One very striking feature of the application of logic to language and to computation is that it requires the combination, the integration and the use of many diverse systems and methodologies - all in the same single application. The papers in this volume will give the reader a glimpse into (...)
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  34.  30
    Computation, Dynamics, and Cognition.Marco Giunti - 1997 - Oxford University Press.
    This book explores the application of dynamical theory to cognitive science. Giunti shows how the dynamical approach can illuminate problems of cognition, information processing, consciousness, meaning, and the relation between body and mind.
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  35. Computation in cognitive science: it is not all about Turing-equivalent computation.Kenneth Aizawa - 2010 - Studies in History and Philosophy of Science Part A 41 (3):227-236.
    It is sometimes suggested that the history of computation in cognitive science is one in which the formal apparatus of Turing-equivalent computation, or effective computability, was exported from mathematical logic to ever wider areas of cognitive science and its environs. This paper, however, indicates some respects in which this suggestion is inaccurate. Computability theory has not been focused exclusively on Turing-equivalent computation. Many essential features of Turing-equivalent computation are not captured in definitions of computation as (...)
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  36. (1 other version)Content, computation, and externalism.Christopher Peacocke - 1994 - Mind and Language 9 (3):227-264.
  37. Computation and hypercomputation.Mike Stannett - 2003 - Minds and Machines 13 (1):115-153.
    Does Nature permit the implementation of behaviours that cannot be simulated computationally? We consider the meaning of physical computation in some detail, and present arguments in favour of physical hypercomputation: for example, modern scientific method does not allow the specification of any experiment capable of refuting hypercomputation. We consider the implications of relativistic algorithms capable of solving the (Turing) Halting Problem. We also reject as a fallacy the argument that hypercomputation has no relevance because non-computable values are indistinguishable from (...)
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  38. The Representational Foundations of Computation.Michael Rescorla - 2015 - Philosophia Mathematica 23 (3):338-366.
    Turing computation over a non-linguistic domain presupposes a notation for the domain. Accordingly, computability theory studies notations for various non-linguistic domains. It illuminates how different ways of representing a domain support different finite mechanical procedures over that domain. Formal definitions and theorems yield a principled classification of notations based upon their computational properties. To understand computability theory, we must recognize that representation is a key target of mathematical inquiry. We must also recognize that computability theory is an intensional enterprise: (...)
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  39.  83
    Copenhagen computation.N. David Mermin - 2003 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 34 (3):511-522.
    I describe a pedagogical scheme devised to teach efficiently to computer scientists just enough quantum mechanics to permit them to understand the theoretical developments of the last decade going under the name of “quantum computation.” I then note that my offbeat approach to quantum mechanics, designed to be maximally efficacious for this specific educational purpose, is nothing other than the Copenhagen interpretation.
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  40. What is computation?B. Jack Copeland - 1996 - Synthese 108 (3):335-59.
    To compute is to execute an algorithm. More precisely, to say that a device or organ computes is to say that there exists a modelling relationship of a certain kind between it and a formal specification of an algorithm and supporting architecture. The key issue is to delimit the phrase of a certain kind. I call this the problem of distinguishing between standard and nonstandard models of computation. The successful drawing of this distinction guards Turing's 1936 analysis of (...) against a difficulty that has persistently been raised against it, and undercuts various objections that have been made to the computational theory of mind. (shrink)
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  41.  77
    Computation and Cognition: Toward a Foundation for Cognitive Science.John Haugeland - 1987 - Philosophy of Science 54 (2):309-311.
  42.  28
    Field Computation in Motor Control.Bruce MacLennan - unknown
    to small scales. Further, it is often useful to describe motor control and sensorimotor coordination in terms of external elds such as force elds and sensory images. We survey the basic concepts of eld computation, including both feed-forward eld operations and eld dynamics resulting from recurrent connections. Adaptive and learning mechanisms are discussed brie y. The application of eld computation to motor control is illustrated by several examples: external force elds associated with spinal neurons, population coding of direction (...)
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  43. Computation and Consciousness.Tim Maudlin - 1989 - Journal of Philosophy 86 (8):407.
  44.  52
    The Computation of Planetary Longitudes in the Zīj of Ibn al-Bannā'.Julio Samsó & Eduardo Millás - 1998 - Arabic Sciences and Philosophy 8 (2):259.
    Ibn al-Bann1321) is the author of one of the four extant of the unfinished zq (fl. Tunis and Marrakesh ca. 1193j accessible for the computation of planetary longitudes. The present paper studies some modifications of the structure of the tables the purpose of which is to make calculations easier. The tables of the planetary and lunar equations of the centre are ' appears as a clever adapter, who displays a clear ingenuity allowing him to introduce formal modifications which give (...)
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  45. The Cognitive Basis of Computation: Putting Computation in Its Place.Daniel D. Hutto, Erik Myin, Anco Peeters & Farid Zahnoun - 2018 - In Mark Sprevak & Matteo Colombo, The Routledge Handbook of the Computational Mind. Routledge. pp. 272-282.
    The mainstream view in cognitive science is that computation lies at the basis of and explains cognition. Our analysis reveals that there is no compelling evidence or argument for thinking that brains compute. It makes the case for inverting the explanatory order proposed by the computational basis of cognition thesis. We give reasons to reverse the polarity of standard thinking on this topic, and ask how it is possible that computation, natural and artificial, might be based on cognition (...)
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  46. Significance of Models of Computation, from Turing Model to Natural Computation.Gordana Dodig-Crnkovic - 2011 - Minds and Machines 21 (2):301-322.
    The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and (...)
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  47. Consciousness, computation, and emotion.Jesse J. Prinz - 2002 - In Simon C. Moore & Mike Oaksford, Consciousness, Emotional Self-Regulation and the Brain. John Benjamins.
  48. Natural Computation Techniques Applications-Using of Intelligent Particle Swarm Optimization Algorithm to Synthesis the Index Modulation Profile of Narrow Ban Fiber Bragg Grating Filter.Yumin Liu & Zhongyuan Yu - 2006 - In O. Stock & M. Schaerf, Lecture Notes In Computer Science. Springer Verlag. pp. 4222--438.
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  49.  55
    Quantum computation and the conscious machine —the reason why computers will never be smarter than people.Peter J. Marcer - 1992 - AI and Society 6 (1):88-93.
  50.  15
    Computation and cognition: Toward a foundation of cognitive science.Mark Stefik - 1989 - Artificial Intelligence 38 (2):241-247.
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