About this topic
Summary The theory of computation is a mathematical theory about the properties of abstract computational objects, such as algorithms and Turing machines. They are abstract in the sense that they ignore or leave out considerations about by features of physical implementations, such as finite memory.  In contrast, computations are done by physical systems: concrete machines made of silicon and metal, or brains made of biological materials, can run algorithms or implement Turing machines. This area is concerned with questions about how the abstract objects that are in the purview of the theory of computation relate to physical systems.
Key works The relationship between abstract computation and physical systems such as brains is a central issue in philosophy of mind, particularly given the rise of computational functionalism as a foundation for the study of the mind.  Here the work of Chalmers 1996 provides a good starting point for bridging the theory of computation with theories of physical systems by means of animplementation relation. 
Introductions A good introduction is Piccinini 2010
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92 found
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  1. To Balance a Pencil on its Tip: On the Passive Approach to Quantum Error Correction.Amit Hagar - manuscript
    Quantum computers are hypothetical quantum information processing (QIP) devices that allow one to store, manipulate, and extract information while harnessing quantum physics to solve various computational problems and do so putatively more efficiently than any known classical counterpart. Despite many ‘proofs of concept’ (Aharonov and Ben–Or 1996; Knill and Laflamme 1996; Knill et al. 1996; Knill et al. 1998) the key obstacle in realizing these powerful machines remains their scalability and susceptibility to noise: almost three decades after their conceptions, experimentalists (...)
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  2. Explaining Experience In Nature: The Foundations Of Logic And Apprehension.Steven Ericsson-Zenith - forthcoming - Institute for Advanced Science & Engineering.
    At its core this book is concerned with logic and computation with respect to the mathematical characterization of sentient biophysical structure and its behavior. -/- Three related theories are presented: The first of these provides an explanation of how sentient individuals come to be in the world. The second describes how these individuals operate. And the third proposes a method for reasoning about the behavior of individuals in groups. -/- These theories are based upon a new explanation of experience in (...)
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  3. What Have Google’s Random Quantum Circuit Simulation Experiments Demonstrated About Quantum Supremacy?Jack K. Horner & John Symons - forthcoming - In Hamid R. Arabnia, Leonidas Deligiannidis, Fernando G. Tinetti & Quoc-Nam Tran (eds.), Advances in Software Engineering, Education, and e-Learning. Cham, Switzerland: Springer Nature.
    Quantum computing is of high interest because it promises to perform at least some kinds of computations much faster than classical computers. Arute et al. 2019 (informally, “the Google Quantum Team”) report the results of experiments that purport to demonstrate “quantum supremacy” – the claim that the performance of some quantum computers is better than that of classical computers on some problems. Do these results close the debate over quantum supremacy? We argue that they do not. In the following, we (...)
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  4. Structure and Dynamics in Implementation of Computations.Jacques Mallah - forthcoming - In Yasemin J. Erden (ed.), Proceedings of the 7th AISB Symposium on Computing and Philosophy:. AISB.
    Without a proper restriction on mappings, virtually any system could be seen as implementing any computation. That would not allow characterization of systems in terms of implemented computations and is not compatible with a computationalist philosophy of mind. Information-based criteria for independence of substates within structured states are proposed as a solution. Objections to the use of requirements for transitions in counterfactual states are addressed, in part using the partial-brain argument as a general counterargument to neural replacement arguments.
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  5. Unrealistic Models for Realistic Computations: How Idealisations Help Represent Mathematical Structures and Found Scientific Computing.Philippos Papayannopoulos - forthcoming - Synthese:1-35.
    We examine two very different approaches to formalising real computation, commonly referred to as “Computable Analysis” and “the BSS approach”. The main models of computation underlying these approaches—bit computation and BSS, respectively—have also been put forward as appropriate foundations for scientific computing. The two frameworks offer useful computability and complexity results about problems whose underlying domain is an uncountable space or \). Since typically the problems dealt with in physical sciences, applied mathematics, economics, and engineering are also defined in uncountable (...)
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  6. How to Infer Explanations From Computer Simulations.Florian J. Boge - 2020 - Studies in History and Philosophy of Science Part A 82:25-33.
    Computer simulations are involved in numerous branches of modern science, and science would not be the same without them. Yet the question of how they can explain real-world processes remains an issue of considerable debate. In this context, a range of authors have highlighted the inferences back to the world that computer simulations allow us to draw. I will first characterize the precise relation between computer and target of a simulation that allows us to draw such inferences. I then argue (...)
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  7. असंभव, अपूर्णता, अपूर्णता, झूठा विरोधाभास, सिद्धांतवाद, गणना की सीमा, एक गैर-क्वांटम यांत्रिक अनिश्चितता सिद्धांत और कंप्यूटर के रूप में ब्रह्मांड पर Wolpert, Chaitin और Wittgenstein ट्यूरिंग मशीन थ्योरी में अंतिम प्रमेय --Wolpert, Chaitin and Wittgenstein on impossibility, incompleteness, the liar paradox, theism, the limits of computation, a non-quantum mechanical uncertainty principle and the universe as computer—the ultimate theorem in Turing Machine Theory (संशोधित 2019).Michael Richard Starks - 2020 - In पृथ्वी पर नर्क में आपका स्वागत है: शिशुओं, जलवायु परिवर्तन, बिटकॉइन, कार्टेल, चीन, लोकतंत्र, विविधता, समानता, हैकर्स, मानव अधिकार, इस्लाम, उदारवाद, समृद्धि, वेब, अराजकता, भुखमरी, बीमारी, हिंसा, कृत्रिम बुद्धिमत्ता, युद्ध. Las Vegas, NV, USA: Reality Press. pp. 215-220.
    मैं कंप्यूटर के रूप में गणना और ब्रह्मांड की सीमा के कई हाल ही में चर्चा पढ़ लिया है, polymath भौतिक विज्ञानी और निर्णय सिद्धांतकार डेविड Wolpert के अद्भुत काम पर कुछ टिप्पणी खोजने की उम्मीद है, लेकिन एक भी प्रशस्ति पत्र नहीं मिला है और इसलिए मैं यह बहुत संक्षिप्त मौजूद सारांश. Wolpert कुछ आश्चर्यजनक असंभव या अधूरापन प्रमेयों साबित कर दिया (1992 से 2008-देखें arxiv dot org) अनुमान के लिए सीमा पर (कम्प्यूटेशन) कि इतने सामान्य वे गणना कर (...)
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  8. Wolpert, Chaitin e Wittgenstein sull'impossibilità, l'incompletezza, il paradosso bugiardo, il teismo, i limiti del calcolo, un principio di incertezza meccanica non quantistica e l'universo come computer, il teorema finale della Teoria della Macchina di Turing (rivisto 2019).Michael Richard Starks - 2020 - In Benvenuti all'inferno sulla Terra: Bambini, Cambiamenti climatici, Bitcoin, Cartelli, Cina, Democrazia, Diversità, Disgenetica, Uguaglianza, Pirati Informatici, Diritti umani, Islam, Liberalismo, Prosperità, Web, Caos, Fame, Malattia, Violenza, Intellige. Las Vegas, NV, USA: Reality Press. pp. 177-181.
    Ho letto molte recenti discussioni sui limiti del calcolo e dell'universo come computer, sperando di trovare alcuni commenti sull'incredibile lavoro del fisico polimatematico e del teorista delle decisioni David Wolpert, ma non ho trovato una sola citazione e quindi presento questo brevissimo riassunto. Wolpert si dimostrò una straordinaria impossibilità o incompletezza teoremi (1992-2008-see arxiv dot org) sui limiti dell'inferenza (calcolo) che sono così generali che sono indipendenti dal dispositivo che fa il calcolo, e anche indipendenti dalle leggi della fisica, in (...)
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  9. Are There Teleological Functions to Compute?Dimitri Coelho Mollo - 2019 - Philosophy of Science 86 (3):431-452.
    I analyze a tension at the core of the mechanistic view of computation generated by its joint commitment to the medium independence of computational vehicles and to computational systems possessing teleological functions to compute. While computation is individuated in medium-independent terms, teleology is sensitive to the constitutive physical properties of vehicles. This tension spells trouble for the mechanistic view, suggesting that there can be no teleological functions to compute. I argue that, once considerations about the relevant function-bestowing factors for computational (...)
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  10. A Simplicity Criterion for Physical Computation.Tyler Millhouse - 2019 - British Journal for the Philosophy of Science 70 (1):153-178.
    The aim of this paper is to offer a formal criterion for physical computation that allows us to objectively distinguish between competing computational interpretations of a physical system. The criterion construes a computational interpretation as an ordered pair of functions mapping (1) states of a physical system to states of an abstract machine, and (2) inputs to this machine to interventions in this physical system. This interpretation must ensure that counterfactuals true of the abstract machine have appropriate counterparts which are (...)
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  11. On the Foundations of Computing.Giuseppe Primiero - 2019 - Oxford University Press.
    Computing, today more than ever before, is a multi-faceted discipline which collates several methodologies, areas of interest, and approaches: mathematics, engineering, programming, and applications. Given its enormous impact on everyday life, it is essential that its debated origins are understood, and that its different foundations are explained. On the Foundations of Computing offers a comprehensive and critical overview of the birth and evolution of computing, and it presents some of the most important technical results and philosophical problems of the discipline, (...)
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  12. Wolpert, Chaitin y Wittgenstein sobre la imposibilidad, la incompletitud, la paradoja mentirosa, el teísmo, los límites de la computación, un principio de incertidumbre mecánica no cuántica y el universo como computadora, el teorema definitivo en la teoría de la máquina de Turing (revisado en 2019).Michael Richard Starks - 2019 - In Delirios Utópicos Suicidas en el Siglo 21 La filosofía, la naturaleza humana y el colapso de la civilización Artículos y reseñas 2006-2019 4a Edición. Las Vegas, NV USA: Reality Press. pp. 278-282.
    He leído muchas discusiones recientes sobre los límites de la computación y el universo como computadora, con la esperanza de encontrar algunos comentarios sobre el increíble trabajo del físico polimatemático y teórico de la decisión David Wolpert pero no han encontrado una sola citación y así que presento esta muy breve Resumen. Wolpert demostró algunos teoremas sorprendentes de imposibilidad o incompletos (1992 a 2008-ver arxiv dot org) en los límites de la inferencia (computación) que son tan generales que son independientes (...)
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  13. Reseña de ' Los Límites Exteriores de la Razón '(The Outer Limits of Reason) por Noson Yanofsky 403p (2013) (revision revisada 2019).Michael Richard Starks - 2019 - In Delirios Utópicos Suicidas en el Siglo 21 La filosofía, la naturaleza humana y el colapso de la civilización Artículos y reseñas 2006-2019 4a Edición. Las Vegas, NV USA: Reality Press. pp. 283-298.
    Doy una revisión detallada de ' los límites externos de la razón ' por Noson Yanofsky desde una perspectiva unificada de Wittgenstein y la psicología evolutiva. Yo indiqué que la dificultad con cuestiones como la paradoja en el lenguaje y las matemáticas, la incompletitud, la indeterminación, la computabilidad, el cerebro y el universo como ordenadores, etc., surgen de la falta de mirada cuidadosa a nuestro uso del lenguaje en el adecuado contexto y, por tanto, el Error al separar los problemas (...)
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  14. Why Computer Simulations Are Not Inferences, and in What Sense They Are Experiments.Florian J. Boge - 2018 - European Journal for Philosophy of Science 9 (1):1-30.
    The question of where, between theory and experiment, computer simulations locate on the methodological map is one of the central questions in the epistemology of simulation. The two extremes on the map have them either be a kind of experiment in their own right, 317–329, 2005; Morrison Philosophical Studies, 143, 33–57, 2009; Morrison 2015; Massimi and Bhimji Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 51, 71–81, 2015; Parker Synthese, 169, 483–496, (...)
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  15. Individuation Without Representation.Joe Dewhurst - 2018 - British Journal for the Philosophy of Science 69 (1):103-116.
    ABSTRACT Shagrir and Sprevak explore the apparent necessity of representation for the individuation of digits in computational systems.1 1 I will first offer a response to Sprevak’s argument that does not mention Shagrir’s original formulation, which was more complex. I then extend my initial response to cover Shagrir’s argument, thus demonstrating that it is possible to individuate digits in non-representational computing mechanisms. I also consider the implications that the non-representational individuation of digits would have for the broader theory of computing (...)
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  16. Complex Organisation and Fundamental Physics.Brian D. Josephson - 2018 - Streaming Media Service, Cambridge University.
    The file on this site provides the slides for a lecture given in Hangzhou in May 2018, and the lecture itself is available at the URL beginning 'sms' in the set of links provided in connection with this item. -/- It is commonly assumed that regular physics underpins biology. Here it is proposed, in a synthesis of ideas by various authors, that in reality structures and mechanisms of a biological character underpin the world studied by physicists, in principle supplying detail (...)
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  17. 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 efficiency, cost, reliability, (...)
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  18. From Computer Metaphor to Computational Modeling: The Evolution of Computationalism.Marcin Miłkowski - 2018 - Minds and Machines 28 (3):515-541.
    In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory (...)
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  19. Functional Individuation, Mechanistic Implementation: The Proper Way of Seeing the Mechanistic View of Concrete Computation.Dimitri Coelho Mollo - 2018 - Synthese 195 (8):3477-3497.
    I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems involves only weak structural constraints, is not enough (...)
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  20. Enactive Autonomy in Computational Systems.Mario Villalobos & Joe Dewhurst - 2018 - Synthese 195 (5):1891-1908.
    In this paper we will demonstrate that a computational system can meet the criteria for autonomy laid down by classical enactivism. The two criteria that we will focus on are operational closure and structural determinism, and we will show that both can be applied to a basic example of a physically instantiated Turing machine. We will also address the question of precariousness, and briefly suggest that a precarious Turing machine could be designed. Our aim in this paper is to challenge (...)
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  21. A Mechanistic Account of Wide Computationalism.Luke Kersten - 2017 - Review of Philosophy and Psychology 8 (3):501-517.
    The assumption that psychological states and processes are computational in character pervades much of cognitive science, what many call the computational theory of mind. In addition to occupying a central place in cognitive science, the computational theory of mind has also had a second life supporting “individualism”, the view that psychological states should be taxonomized so as to supervene only on the intrinsic, physical properties of individuals. One response to individualism has been to raise the prospect of “wide computational systems”, (...)
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  22. There’s Plenty of Boole at the Bottom: A Reversible CA Against Information Entropy.Francesco Berto, Jacopo Tagliabue & Gabriele Rossi - 2016 - Minds and Machines 26 (4):341-357.
    “There’s Plenty of Room at the Bottom”, said the title of Richard Feynman’s 1959 seminal conference at the California Institute of Technology. Fifty years on, nanotechnologies have led computer scientists to pay close attention to the links between physical reality and information processing. Not all the physical requirements of optimal computation are captured by traditional models—one still largely missing is reversibility. The dynamic laws of physics are reversible at microphysical level, distinct initial states of a system leading to distinct final (...)
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  23. Why Build a Virtual Brain? Large-Scale Neural Simulations as Jump Start for Cognitive Computing.Matteo Colombo - 2016 - Journal of Experimental and Theoretical Artificial Intelligence.
    Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates (...)
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  24. 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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  25. 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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  26. Ed Fredkin and the Physics of Information - An Inside Story of an Outsider Scientist.Amit Hagar - 2016 - Information and Culture 51 (3):419-443.
    This article tells the story of Ed Fredkin, a pilot, programmer, engineer, hardware designer and entrepreneur, whose work inside and outside academia has influenced major developments in computer science and in the foundations of theoretical physics for the past fifty years.
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  27. Computation and Multiple Realizability.Marcin Miłkowski - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. 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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  28. DDoS Protection With IPtables.Constantin Oesterling - 2016 - InfoSec:15.
    Research on the most effective Linux iptables rules to mitigate Distributed Denial of Service (DDoS) attacks.
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  29. 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 to (...)
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  30. Review of Computability: Turing, Gödel, Church, and Beyond. [REVIEW]Andrew Arana - 2015 - Notre Dame Philosophical Reviews 3 (20).
  31. Utopias and Dystopias as Cybernetic Information Systems: Envisioning the Posthuman Neuropolity.Matthew E. Gladden - 2015 - Creatio Fantastica (3 (50)).
    While it is possible to understand utopias and dystopias as particular kinds of sociopolitical systems, in this text we argue that utopias and dystopias can also be understood as particular kinds of information systems in which data is received, stored, generated, processed, and transmitted by the minds of human beings that constitute the system’s ‘nodes’ and which are connected according to specific network topologies. We begin by formulating a model of cybernetic information-processing properties that characterize utopias and dystopias. It is (...)
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  32. The World is Either Digital or Analogue.Francesco Berto & Jacopo Tagliabue - 2014 - Synthese 191 (3):481-497.
    We address an argument by Floridi (Synthese 168(1):151–178, 2009; 2011a), to the effect that digital and analogue are not features of reality, only of modes of presentation of reality. One can therefore have an informational ontology, like Floridi’s Informational Structural Realism, without commitment to a supposedly digital or analogue world. After introducing the topic in Sect. 1, in Sect. 2 we explain what the proposition expressed by the title of our paper means. In Sect. 3, we describe Floridi’s argument. In (...)
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  33. Erratum To: A Revised Attack on Computational Ontology. [REVIEW]Nir Fresco & Phillip J. Staines - 2014 - Minds and Machines 24 (1):141-141.
    Erratum to: Minds & Machines DOI 10.1007/s11023-013-9327-1Acknowledgment was omitted from the original publication of this article, and appears below.
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  34. The Instructional Information Processing Account of Digital Computation.Nir Fresco & Marty J. Wolf - 2014 - Synthese 191 (7):1469-1492.
    What is nontrivial digital computation? It is the processing of discrete data through discrete state transitions in accordance with finite instructional information. The motivation for our account is that many previous attempts to answer this question are inadequate, and also that this account accords with the common intuition that digital computation is a type of information processing. We use the notion of reachability in a graph to defend this characterization in memory-based systems and underscore the importance of instructional information for (...)
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  35. Concrete Digital Computation: Competing Accounts and its Role in Cognitive Science.Nir Fresco - 2013 - Dissertation, University of New South Wales
    There are currently considerable confusion and disarray about just how we should view computationalism, connectionism and dynamicism as explanatory frameworks in cognitive science. A key source of this ongoing conflict among the central paradigms in cognitive science is an equivocation on the notion of computation simpliciter. ‘Computation’ is construed differently by computationalism, connectionism, dynamicism and computational neuroscience. I claim that these central paradigms, properly understood, can contribute to an integrated cognitive science. Yet, before this claim can be defended, a better (...)
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  36. Eric Winsberg: Science in the Age of Computer Simulation: The University of Chicago Press, Chicago, IL, 2010, 168 Pp., $ 24.00 , ISBN: 978-0-226-90204-3. [REVIEW]Stefan Gruner - 2013 - Minds and Machines 23 (2):251-254.
  37. Review of Probably Approximately Correct. [REVIEW]Christopher Mole - 2013 - TLS: The Times Literary Supplement 5772:32.
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  38. What is a Digital State?Vincent C. Müller - 2013 - In Mark J. Bishop & Yasemin Erden (eds.), The Scandal of Computation - What is Computation? - AISB Convention 2013. AISB. pp. 11-16.
    There is much discussion about whether the human mind is a computer, whether the human brain could be emulated on a computer, and whether at all physical entities are computers (pancomputationalism). These discussions, and others, require criteria for what is digital. I propose that a state is digital if and only if it is a token of a type that serves a particular function - typically a representational function for the system. This proposal is made on a syntactic level, assuming (...)
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  39. Solving Ordinary Differential Equations by Working with Infinitesimals Numerically on the Infinity Computer.Yaroslav Sergeyev - 2013 - Applied Mathematics and Computation 219 (22):10668–10681.
    There exists a huge number of numerical methods that iteratively construct approximations to the solution y(x) of an ordinary differential equation (ODE) y′(x) = f(x,y) starting from an initial value y_0=y(x_0) and using a finite approximation step h that influences the accuracy of the obtained approximation. In this paper, a new framework for solving ODEs is presented for a new kind of a computer – the Infinity Computer (it has been patented and its working prototype exists). The new computer is (...)
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  40. The Nature of Computational Things.Franck Varenne - 2013 - In Frédéric Migayrou Brayer & Marie-Ange (eds.), Naturalizing Architecture. Orléans: HYX Editions. pp. 96-105.
    Architecture often relies on mathematical models, if only to anticipate the physical behavior of structures. Accordingly, mathematical modeling serves to find an optimal form given certain constraints, constraints themselves translated into a language which must be homogeneous to that of the model in order for resolution to be possible. Traditional modeling tied to design and architecture thus appears linked to a topdown vision of creation, of the modernist, voluntarist and uniformly normative type, because usually (mono)functionalist. One available instrument of calculation/representation/prescription (...)
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  41. Cellular Automata.Francesco Berto & Jacopo Tagliabue - 2012 - Stanford Encyclopedia of Philosophy.
    Cellular automata (henceforth: CA) are discrete, abstract computational systems that have proved useful both as general models of complexity and as more specific representations of non-linear dynamics in a variety of scientific fields. Firstly, CA are (typically) spatially and temporally discrete: they are composed of a finite or denumerable set of homogeneous, simple units, the atoms or cells. At each time unit, the cells instantiate one of a finite set of states. They evolve in parallel at discrete time steps, following (...)
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  42. Proving Darwin: Making Biology Mathematical.G. J. Chaitin - 2012 - Pantheon.
    Groundbreaking mathematician Gregory Chaitin gives us the first book to posit that we can prove how Darwin’s theory of evolution works on a mathematical level.
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  43. The Role of 'Complex' Empiricism in the Debates About Satellite Data and Climate Models.Elisabeth A. Lloyd - 2012 - Studies in History and Philosophy of Science Part A 43 (2):390-401.
    climate scientists have been engaged in a decades-long debate over the standing of satellite measurements of the temperature trends of the atmosphere above the surface of the earth. This is especially significant because skeptics of global warming and the greenhouse effect have utilized this debate to spread doubt about global climate models used to predict future states of climate. I use this case from an under-studied science to illustrate two distinct philosophical approaches to the relation among data, scientists, measurement, models, (...)
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  44. Client-Server Based Remote Access Through the Internet: Internet Based Remote Process Control.Mohammed Abdullah Hussein - 2011 - Germany: LAP Lambert Academic Publishing.
    Internet based process control usage has grown in the past years. Industry field demands were behind this, and it ranges from factory, office and home automation to tasks simplifications and cost reduction. In this book a hardware interface circuit and a software system used to control the temperature and level of a liquid tank is described. The advantage of the designed interface circuit is its simplicity and low cost. The same can be true for the software system in which we (...)
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  45. Agent-Based Modeling: The Right Mathematics for the Social Sciences?Paul L. Borrill & Leigh Tesfatsion - 2011 - In J. B. Davis & D. W. Hands (eds.), Elgar Companion to Recent Economic Methodology. Edward Elgar Publishers. pp. 228.
    This study provides a basic introduction to agent-based modeling (ABM) as a powerful blend of classical and constructive mathematics, with a primary focus on its applicability for social science research. The typical goals of ABM social science researchers are discussed along with the culture-dish nature of their computer experiments. The applicability of ABM for science more generally is also considered, with special attention to physics. Finally, two distinct types of ABM applications are summarized in order to illustrate concretely the duality (...)
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  46. Some Philosophical Issues in Computer Science.Amnon H. Eden - 2011 - Minds and Machines 21 (2):123-133.
    The essays included in the special issue dedicated to the philosophy of computer science examine new philosophical questions that arise from reflection upon conceptual issues in computer science and the insights such an enquiry provides into ongoing philosophical debates.
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  47. A Note on the Physical Possibility of Transfinite Computation.Wayne Aitken & Jeffrey A. Barrett - 2010 - British Journal for the Philosophy of Science 61 (4):867-874.
    In this note, we consider constraints on the physical possibility of transfinite Turing machines that arise from how one models the continuous structure of space and time in one's best physical theories. We conclude by suggesting a version of Church's thesis appropriate as an upper bound for physical computation given how space and time are modeled on our current physical theories.
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  48. Dynamic Mechanistic Explanation: Computational Modeling of Circadian Rhythms as an Exemplar for Cognitive Science.William Bechtel & Adele Abrahamsen - 2010 - Studies in History and Philosophy of Science Part A 41 (3):321-333.
    Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction with their (...)
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  49. Indistinguishable From Magic: Computation is Cognitive Technology. [REVIEW]John Kadvany - 2010 - Minds and Machines 20 (1):119-143.
    This paper explains how mathematical computation can be constructed from weaker recursive patterns typical of natural languages. A thought experiment is used to describe the formalization of computational rules, or arithmetical axioms, using only orally-based natural language capabilities, and motivated by two accomplishments of ancient Indian mathematics and linguistics. One accomplishment is the expression of positional value using versified Sanskrit number words in addition to orthodox inscribed numerals. The second is Pāṇini’s invention, around the fifth century BCE, of a formal (...)
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  50. Violation of Local Realism with Freedom of Choice.T. Scheidl, R. Ursin, J. Kofler, S. Ramelow, X. Ma, T. Herbst, L. Ratschbacher, A. Fedrizzi, N. K. Langford, T. Jennewein & A. Zeilinger - 2010 - Pnas 107 (46):19709-19713.
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