Results for 'computation'

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  1. Computer Science Logic 11th International Workshop, Csl '97 : Annual Conference of the Eacsl, Aarhus, Denmark, August 23-29, 1997 : Procedings. [REVIEW]M. Nielsen, Wolfgang Thomas & European Association for Computer Science Logic - 1998
     
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  2.  1
    Computer Science Logic: 10th International Workshop, Csl '96, Annual Conference of the Eacsl, Utrecht, the Netherlands, September 21 - 27, 1996, Selected Papers. [REVIEW]D. van Dalen, M. Bezem & European Association for Computer Science Logic - 1997 - Springer Verlag.
    The related fields of fractal image encoding and fractal image analysis have blossomed in recent years. This book, originating from a NATO Advanced Study Institute held in 1995, presents work by leading researchers. It is developing the subjects at an introductory level, but it also has some recent and exciting results in both fields. The book contains a thorough discussion of fractal image compression and decompression, including both continuous and discrete formulations, vector space and hierarchical methods, and algorithmic optimizations. The (...)
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  3.  1
    Discrete Mathematics and Theoretical Computer Science 4th International Conference, Dmtcs 2003, Dijon, France, July 2003, Proceedings. [REVIEW]Cristian Calude, M. J. Dinneen & Vincent Vajnovszki - 2003 - Springer Verlag.
    The fourthDiscrete Mathematics andTheoreticalComputer Science Conference was jointly organized by the Centre for Discrete Mathematics and Theoretical Computer Science of the University of Auckland and the University of Bourgogne in Dijon, France, and took place in Dijon from 7 to12 July2003.Thepreviousconferenceswereheld inAuckland,NewZealand and Constan ̧ ta, Romania. The?ve invited speakers of the conference were: G.J. Chaitin, C. Ding, S. Istrail, M. Margenstein, and T. Walsh. The Programme Committee, consisting of V. Berthe, S. Boza- lidis,C.S.Calude,V.E.Cazanescu, F. Cucker, M. Deza, J. Diaz, (...)
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  4.  8
    Computational Indeterminacy and Explanations in Cognitive Science.Philippos Papayannopoulos, Nir Fresco & Oron Shagrir - 2022 - Biology and Philosophy 37 (6):1-30.
    Computational physical systems may exhibit indeterminacy of computation (IC). Their identified physical dynamics may not suffice to select a unique computational profile. We consider this phenomenon from the point of view of cognitive science and examine how computational profiles of cognitive systems are identified and justified in practice, in the light of IC. To that end, we look at the literature on the underdetermination of theory by evidence and argue that the same devices that can be successfully employed to (...)
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  5.  56
    Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization.Richard L. Lewis, Andrew Howes & Satinder Singh - 2014 - Topics in Cognitive Science 6 (2):279-311.
    We propose a framework for including information-processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of (...)
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  6. Artificial Intelligence and Symbolic Computation: International Conference Aisc 2000 Madrid, Spain, July 17-19, 2000. Revised Papers. [REVIEW]International Conference Aisc & John A. Campbell - 2001 - Springer Verlag.
    This book constitutes the thoroughly refereed post-proceedings of the International Conference on Artificial Intelligence and Symbolic Computation, AISC 2000, held in Madrid, Spain in July 2000. The 17 revised full papers presented together with three invited papers were carefully reviewed and revised for inclusion in the book. Among the topics addressed are automated theorem proving, logical reasoning, mathematical modeling of multi-agent systems, expert systems and machine learning, computational mathematics, engineering, and industrial applications.
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  7. European Computing and Philosophy.Gordana Dodig-Crnkovic - 2009 - The Reasoner 3 (9):18-19.
    European Computing and Philosophy conference, 2–4 July Barcelona The Seventh ECAP (European Computing and Philosophy) conference was organized by Jordi Vallverdu at Autonomous University of Barcelona. The conference started with the IACAP (The International Association for CAP) presidential address by Luciano Floridi, focusing on mechanisms of knowledge production in informational networks. The first keynote delivered by Klaus Mainzer made a frame for the rest of the conference, by elucidating the fundamental role of complexity of informational structures that can be analyzed (...)
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  8. Computational Theory of Mind.Marcin Milkowski - 2013
    The Computational Theory of Mind The Computational Theory of Mind (CTM) claims that the mind is a computer, so the theory is also known as computationalism. It is generally assumed that CTM is the main working hypothesis of cognitive science. CTM is often understood as a specific variant of the Representational Theory of Mind (RTM), […].
     
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  9. Cognitive Computation Sans Representation.Paul Schweizer - 2017 - In Thomas Powers (ed.), Philosophy and Computing: Essays in epistemology, philosophy of mind, logic, and ethics,. Cham, Switzerland: Springer. pp. 65-84.
    The Computational Theory of Mind (CTM) holds that cognitive processes are essentially computational, and hence computation provides the scientific key to explaining mentality. The Representational Theory of Mind (RTM) holds that representational content is the key feature in distinguishing mental from non-mental systems. I argue that there is a deep incompatibility between these two theoretical frameworks, and that the acceptance of CTM provides strong grounds for rejecting RTM. The focal point of the incompatibility is the fact that representational content (...)
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  10.  41
    Computational Principles of Working Memory in Sentence Comprehension.Richard L. Lewis, Shravan Vasishth & Julie A. Van Dyke - 2006 - Trends in Cognitive Sciences 10 (10):447-454.
  11.  18
    The Computational Boundary of a “Self”: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition.Michael Levin - 2019 - Frontiers in Psychology 10.
  12. A Computable Universe: Understanding and Exploring Nature as Computation.Hector Zenil - unknown
    A Computable Universe is a collection of papers discussing computation in nature and the nature of computation, a compilation of the views of the pioneers in the contemporary area of intellectual inquiry focused on computational and informational theories of the world. This volume is the definitive source of informational/computational views of the world, and of cutting-edge models of the universe, both digital and quantum, discussed from a philosophical perspective as well as in the greatest technical detail. The book (...)
     
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  13. Why Computers Are Not Intelligent: An Argument.Richard Oxenberg - 2017 - Political Animal Magazine.
    Computers can mimic human intelligence, sometimes quite impressively. This has led some to claim that, a.) computers can actually acquire intelligence, and/or, b.) the human mind may be thought of as a very sophisticated computer. In this paper I argue that neither of these inferences are sound. The human mind and computers, I argue, operate on radically different principles.
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  14.  3
    Computability and Randomness.André Nies - 2008 - Oxford, England: Oxford University Press UK.
    The interplay between computability and randomness has been an active area of research in recent years, reflected by ample funding in the USA, numerous workshops, and publications on the subject. The complexity and the randomness aspect of a set of natural numbers are closely related. Traditionally, computability theory is concerned with the complexity aspect. However, computability theoretic tools can also be used to introduce mathematical counterparts for the intuitive notion of randomness of a set. Recent research shows that, conversely, concepts (...)
  15. Computer, Proof, and Testimony.Kai-Yee Wong - 2012 - Studies in Logic 5 (1):50-67.
    It has been claimed that computer-assisted proof utilizes empirical evidence in a manner unheard of in traditional mathematics and therefore its employment forces us to modify our conception of proof. This paper provides a critical survey of some arguments for this claim. It starts by revisiting a well known paper by Thomas Tymoczko on the computer proof of the Four-Color Theorem. Drawing on some ideas from the works of Tyler Burge and others, it then considers a way to see the (...)
     
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  16.  39
    Computation and Automata.Arto Salomaa - 1985 - Cambridge University Press.
    This introduction to certain mathematical topics central to theoretical computer science treats computability and recursive functions, formal languages and automata, computational complexity, and cruptography. The presentation is essentially self-contained with detailed proofs of all statements provided. Although it begins with the basics, it proceeds to some of the most important recent developments in theoretical computer science.
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  17. Cognition, Computing and Dynamic Systems.Mario Villalobos & Joe Dewhurst - 2016 - Límite. Revista Interdisciplinaria de Filosofía y Psicología 1.
    Traditionally, computational theory (CT) and dynamical systems theory (DST) have presented themselves as opposed and incompatible paradigms in cognitive science. There have been some efforts to reconcile these paradigms, mainly, by assimilating DST to CT at the expenses of its anti-representationalist commitments. In this paper, building on Piccinini’s mechanistic account of computation and the notion of functional closure, we explore an alternative conciliatory strategy. We try to assimilate CT to DST by dropping its representationalist commitments, and by inviting CT (...)
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  18.  9
    Computability and Logic.George S. Boolos, John P. Burgess & Richard C. Jeffrey - 1974 - Cambridge, England: Cambridge University Press.
    Computability and Logic has become a classic because of its accessibility to students without a mathematical background and because it covers not simply the staple topics of an intermediate logic course, such as Godel's incompleteness theorems, but also a large number of optional topics, from Turing's theory of computability to Ramsey's theorem. This 2007 fifth edition has been thoroughly revised by John Burgess. Including a selection of exercises, adjusted for this edition, at the end of each chapter, it offers a (...)
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  19. Computability and Logic.George Boolos, John Burgess, Richard P. & C. Jeffrey - 2002 - Cambridge University Press.
    Computability and Logic has become a classic because of its accessibility to students without a mathematical background and because it covers not simply the staple topics of an intermediate logic course, such as Godel’s incompleteness theorems, but also a large number of optional topics, from Turing’s theory of computability to Ramsey’s theorem. Including a selection of exercises, adjusted for this edition, at the end of each chapter, it offers a new and simpler treatment of the representability of recursive functions, a (...)
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  20.  32
    Computability and Complexity: From a Programming Perspective Vol. 21.N. D. Jones - 1997 - MIT Press.
    This makes his book especially valuable." -- Yuri Gurevich, Professor of Computer Science, University of Michigan Computability and complexity theory should be of central concern to practitioners as well as theorists.
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  21. Morphological Computation: Nothing but Physical Computation.Marcin Miłkowski - 2018 - Entropy 10 (20):942.
    The purpose of this paper is to argue against the claim that morphological computation is substantially different from other kinds of physical computation. I show that some (but not all) purported cases of morphological computation do not count as specifically computational, and that those that do are solely physical computational systems. These latter cases are not, however, specific enough: all computational systems, not only morphological ones, may (and sometimes should) be studied in various ways, including their energy (...)
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  22. Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientiae 18:215-228.
    In most accounts of realization of computational processes by physical mechanisms, it is presupposed that there is one-to-one correspondence between the causally active states of the physical process and the states of the computation. Yet such proposals either stipulate that only one model of computation is implemented, or they do not reflect upon the variety of models that could be implemented physically. -/- In this paper, I claim that mechanistic accounts of computation should allow for a broad (...)
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  23. Computing and Philosophy: Selected Papers From IACAP 2014.Vincent C. Müller (ed.) - 2016 - Springer.
    This volume offers very selected papers from the 2014 conference of the “International Association for Computing and Philosophy” (IACAP) - a conference tradition of 28 years. - - - Table of Contents - 0 Vincent C. Müller: - Editorial - 1) Philosophy of computing - 1 Çem Bozsahin: - What is a computational constraint? - 2 Joe Dewhurst: - Computing Mechanisms and Autopoietic Systems - 3 Vincenzo Fano, Pierluigi Graziani, Roberto Macrelli and Gino Tarozzi: - Are Gandy Machines really local? (...)
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  24. Computer-Assisted Argument Mapping: A Rationale Approach.Martin Davies - 2009 - Higher Education 58:799-820.
    Computer-Assisted Argument Mapping (CAAM) is a new way of understanding arguments. While still embryonic in its development and application, CAAM is being used increasingly as a training and development tool in the professions and government. Inroads are also being made in its application within education. CAAM claims to be helpful in an educational context, as a tool for students in responding to assessment tasks. However, to date there is little evidence from students that this is the case. This paper outlines (...)
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  25.  2
    Computing and Philosophy in Asia.Soraj Hongladarom (ed.) - 2007 - Cambridge Scholars Press.
    This volume is a collection of selected papers presented at the Second Asia-Pacific Computing and Philsosophy Conference, which was held in Bangkok, Thailand in January 2005. The conference was organized by the Center for Ethics of Science and Technology, Chulalongkorn University on behalf of the International Association of Computing and Philosophy (www.ia-cap.org). Computing have had a long relationship with philosophy, starting from the problem of how symbols being manipulated in computing bear a relation to the outside world, to those of (...)
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  26.  60
    Computational Modeling as a Philosophical Methodology.Patrick Grim - 2003 - In Luciano Floridi (ed.), The Blackwell Guide to the Philosophy of Computing and Information. Blackwell. pp. 337--349.
    Since the sixties, computational modeling has become increasingly important in both the physical and the social sciences, particularly in physics, theoretical biology, sociology, and economics. Sine the eighties, philosophers too have begun to apply computational modeling to questions in logic, epistemology, philosophy of science, philosophy of mind, philosophy of language, philosophy of biology, ethics, and social and political philosophy. This chapter analyzes a selection of interesting examples in some of those areas.
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  27. Quantum Computing.Amit Hagar & Michael Cuffaro - 2019 - Stanford Encyclopedia of Philosophy.
    Combining physics, mathematics and computer science, quantum computing and its sister discipline of quantum information have developed in the past few decades from visionary ideas to two of the most fascinating areas of quantum theory. General interest and excitement in quantum computing was initially triggered by Peter Shor (1994) who showed how a quantum algorithm could exponentially “speed-up” classical computation and factor large numbers into primes far more efficiently than any (known) classical algorithm. Shor’s algorithm was soon followed by (...)
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  28. A Computational Foundation for the Study of Cognition.David Chalmers - 2011 - Journal of Cognitive Science 12 (4):323-357.
    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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  29. Unconventional Computing, Arts, Philosophy.Andrew Adamatzky (ed.) - 2022 - World Scientific Publishing Company.
    The unique compendium re-assesses the value of future and emergent computing technologies via artistic and philosophical means. The book encourages scientists to adopt inspiring thinking of artists and philosophers to reuse scientific concepts in their works.The useful reference text consists of non-typical topics, where artistic and philosophical concepts encourage readers to adopt unconventional approaches towards computing and immerse themselves into discoveries of future emerging landscape.
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  30.  11
    Quantum Computation and Quantum Information.Michael A. Nielsen, Isaac L. Chuang & Isaac L. Chuang - 2000 - Cambridge University Press.
    First-ever comprehensive introduction to the major new subject of quantum computing and quantum information.
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  31. Why Computers Can't Act.Lynne Rudder Baker - 1981 - American Philosophical Quarterly 18 (2):157-163.
    To be an agent, one must be able to formulate intentions. To be able to formulate intentions, one must have a first-person perspective. Computers lack a first-person perspective. So, computers are not agents.
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  32. Understanding Computation Time : A Critical Discussion of Time as a Computational Performance Metric.David Harris-Birtill & Rose Harris-Birtill - 2021 - In Arkadiusz Misztal, Paul Harris & Jo Alyson Parker (eds.), Time in variance. Brill.
     
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  33. Computation, Laws and Supervenience.Terrance Tomkow - manuscript
    The Computational Theory of the Laws of Nature entails that the accessibility relation for nomological necessity is not symmetric or transitive. This means that nomologically possible worlds need not share our world's laws. This subverts a standard style of argument against Humean Supervenience.
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  34.  64
    A Computational Approach to Quantifiers as an Explanation for Some Language Impairments in Schizophrenia.Marcin Zajenkowski, Rafał Styła & Jakub Szymanik - 2011 - Journal of Communication Disorder 44:2011.
    We compared the processing of natural language quantifiers in a group of patients with schizophrenia and a healthy control group. In both groups, the difficulty of the quantifiers was consistent with computational predictions, and patients with schizophrenia took more time to solve the problems. However, they were significantly less accurate only with proportional quantifiers, like more than half. This can be explained by noting that, according to the complexity perspective, only proportional quantifiers require working memory engagement.
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  35. Cloud Computing and its Ethical Challenges.Matteo Turilli & Luciano Floridi - manuscript
    The paper analyses six ethical challenges posed by cloud computing, concerning ownership, safety, fairness, responsibility, accountability and privacy. The first part defines cloud computing on the basis of a resource-oriented approach, and outlines the main features that characterise such technology. Following these clarifications, the second part argues that cloud computing reshapes some classic problems often debated in information and computer ethics. To begin with, cloud computing makes possible a complete decoupling of ownership, possession and use of data and this helps (...)
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  36.  21
    Computability in Context: Computation and Logic in the Real World.S. B. Cooper & Andrea Sorbi (eds.) - 2011 - World Scientific.
    Recent new paradigms of computation, based on biological and physical models, address in a radically new way questions of efficiency and challenge assumptions ...
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  37. Computable Rationality, NUTS, and the Nuclear Leviathan.S. M. Amadae - 2018 - In Daniel Bessner & Nicolas Guilhot (eds.), The Decisionist Imagination: Democracy, Sovereignty and Social Science in the 20th Century. New York, NY, USA:
    This paper explores how the Leviathan that projects power through nuclear arms exercises a unique nuclearized sovereignty. In the case of nuclear superpowers, this sovereignty extends to wielding the power to destroy human civilization as we know it across the globe. Nuclearized sovereignty depends on a hybrid form of power encompassing human decision-makers in a hierarchical chain of command, and all of the technical and computerized functions necessary to maintain command and control at every moment of the sovereign's existence: this (...)
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  38. The Computational Theory of Mind.John-Michael Kuczynski - 2014 - Madison, WI, USA: Philosophypedia.
    The widespread belief that the mind is a computer embodies a failure to distinguish between computers and information-processing systems. Minds are information-processing systems, but they are not computers.
     
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  39.  76
    Computational Complexity of Some Ramsey Quantifiers in Finite Models.Marcin Mostowski & Jakub Szymanik - 2007 - Bulletin of Symbolic Logic 13:281--282.
    The problem of computational complexity of semantics for some natural language constructions – considered in [M. Mostowski, D. Wojtyniak 2004] – motivates an interest in complexity of Ramsey quantifiers in finite models. In general a sentence with a Ramsey quantifier R of the following form Rx, yH(x, y) is interpreted as ∃A(A is big relatively to the universe ∧A2 ⊆ H). In the paper cited the problem of the complexity of the Hintikka sentence is reduced to the problem of computational (...)
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  40.  2
    Philosophy and Computer Science.Timothy Colburn - 2000 - Routledge.
    Colburn has a doctorate in philosophy and an advanced degree in computer science; he's worked as a philosophy professor, a computer programmer, and a research scientist in artificial intelligence. Here he discusses the philosophical foundations of artificial intelligence; the new encounter of science and philosophy ; and the philosophy of computer science.
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  41. Digital Theology: A Computer Science Perspective.Erkki Sutinen - 2021 - Bingley, U.K.: Emerald Publishing.
    Introduction: towards a dialogue of the theological and the computational -- What is digital theology? -- Why explore digital theology? -- How to research digital theology? -- What might the future of digital theology look like? -- Conclusion.
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  42.  24
    On Computable Numbers, Non-Universality, and the Genuine Power of Parallelism.Nancy Salay & Selim Akl - 2015 - International Journal of Unconventional Computing 11 (3-4):283-297.
    We present a simple example that disproves the universality principle. Unlike previous counter-examples to computational universality, it does not rely on extraneous phenomena, such as the availability of input variables that are time varying, computational complexity that changes with time or order of execution, physical variables that interact with each other, uncertain deadlines, or mathematical conditions among the variables that must be obeyed throughout the computation. In the most basic case of the new example, all that is used is (...)
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  43.  24
    Computational Lexical Semantics.Patrick Saint-Dizier & Evelyn Viegas (eds.) - 1995 - Cambridge University Press.
    Lexical semantics has become a major research area within computational linguistics, drawing from psycholinguistics, knowledge representation, computer algorithms and architecture. Research programmes whose goal is the definition of large lexicons are asking what the appropriate representation structure is for different facets of lexical information. Among these facets, semantic information is probably the most complex and the least explored.Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerised lexicons for the automatic (...)
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  44. Computers, Dynamical Systems, Phenomena, and the Mind.Marco Giunti - 1992 - Dissertation, Indiana University
    This work addresses a broad range of questions which belong to four fields: computation theory, general philosophy of science, philosophy of cognitive science, and philosophy of mind. Dynamical system theory provides the framework for a unified treatment of these questions. ;The main goal of this dissertation is to propose a new view of the aims and methods of cognitive science--the dynamical approach . According to this view, the object of cognitive science is a particular set of dynamical systems, which (...)
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  45.  10
    Computational Topic Models for Theological Investigations.Mark Graves - 2022 - Theology and Science 20 (1):69-84.
    Sallie McFague’s theological models construct a tensive relationship between conceptual structures and symbolic, metaphorical language to interpret the defining and elusive aspects of theological phenomena and loci. Computational models of language can extend and formalize the conceptual structures of theological models to develop computer-augmented interpretations of theological texts. Previously unclear is whether computational models can retain the tensive symbolism essential for theological investigation. I demonstrate affirmatively by constructing a computational topic model of the moral theology of Thomas Aquinas from Summa (...)
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  46. Quantum Computer: Quantum Model and Reality.Vasil Penchev - 2020 - Epistemology eJournal (Elsevier: SSRN) 13 (17):1-7.
    Any computer can create a model of reality. The hypothesis that quantum computer can generate such a model designated as quantum, which coincides with the modeled reality, is discussed. Its reasons are the theorems about the absence of “hidden variables” in quantum mechanics. The quantum modeling requires the axiom of choice. The following conclusions are deduced from the hypothesis. A quantum model unlike a classical model can coincide with reality. Reality can be interpreted as a quantum computer. The physical processes (...)
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  47.  22
    Computing is at Best a Special Kind of Thinking.James H. Fetzer - 2000 - In The Proceedings of the Twentieth World Congress of Philosophy. Charlottesville: Philosophy Doc Ctr. pp. 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 (or “signusing”) systems for which signs stand for other things for (...)
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  48. Why Computers Must Have Bodies in Order to Be Intelligent.Hubert L. Dreyfus - 1967 - Review of Metaphysics 21 (1):13-32.
    IN SEPTEMBER 1957, Herbert Simon, a pioneer in cognitive simulation, predicted that within ten years, i.e., by now, a computer would be world chess champion and would prove an important mathematical theorem. This prediction was based on Simon's early initial success in writing a program that could play legal chess and one able to prove simple theorems in logic and geometry. But the early successes turned out to be based on the solution of problems that were simple for machines, and (...)
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  49. Computing Mechanisms and Autopoietic Systems.Joe Dewhurst - 2016 - In Vincent Müller (ed.), Computing and Philosophy. Springer Verlag. pp. 17-26.
    This chapter draws an analogy between computing mechanisms and autopoietic systems, focusing on the non-representational status of both kinds of system (computational and autopoietic). It will be argued that the role played by input and output components in a computing mechanism closely resembles the relationship between an autopoietic system and its environment, and in this sense differs from the classical understanding of inputs and outputs. The analogy helps to make sense of why we should think of computing mechanisms as non-representational, (...)
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  50.  89
    Computation, Information, Cognition: The Nexus and the Liminal.F.Gordana Dodig Crnkovic & Susan Stuart (eds.) - 2007 - Cambridge Scholars Press.
    Written by world-leading experts, this book draws together a number of important strands in contemporary approaches to the philosophical and scientific questions that emerge when dealing with the issues of computing, information, cognition and the conceptual issues that arise at their intersections. It discovers and develops the connections at the borders and in the interstices of disciplines and debates. This volume presents a range of essays that deal with the currently vigorous concerns of the philosophy of information, ontology creation and (...)
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