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  1. 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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  2. The Formats of Cognitive Representation: A Computational Account.Dimitri Coelho Mollo & Alfredo Vernazzani - 2023 - Philosophy of Science (3):682-701.
    Cognitive representations are typically analysed in terms of content, vehicle and format. While current work on formats appeals to intuitions about external representations, such as words and maps, in this paper we develop a computational view of formats that does not rely on intuitions. In our view, formats are individuated by the computational profiles of vehicles, i.e., the set of constraints that fix the computational transformations vehicles can undergo. The resulting picture is strongly pluralistic, it makes space for a variety (...)
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  3. What Have Google’s Random Quantum Circuit Simulation Experiments Demonstrated about Quantum Supremacy?Jack K. Horner & John Symons - 2021 - In Hamid R. Arabnia, Leonidas Deligiannidis, Fernando G. Tinetti & Quoc-Nam Tran (eds.), Advances in Software Engineering, Education, and E-Learning: Proceedings From Fecs'20, Fcs'20, Serp'20, and Eee'20. Springer.
    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. (1 other version)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. Ls 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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  5. 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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  6. 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 4TH Edición. 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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  7. (1 other version)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 4TH Edición. 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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  8. 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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  9. 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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  10. 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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  11. 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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  12. 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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  13. 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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  14. (1 other version)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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  15. Computing Mechanisms and Autopoietic Systems.Joe Dewhurst - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: Springer. 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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  16. Computation and Multiple Realizability.Marcin Miłkowski - 2016 - In Vincent C. Müller (ed.), 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. Review of Probably Approximately Correct. [REVIEW]Christopher Mole - 2013 - TLS: The Times Literary Supplement 5772:32.
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  22. 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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  23. 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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  24. The Nature of Computational Things.Franck Varenne - 2013 - In Frédéric Migayrou Brayer & Marie-Ange (eds.), Naturalizing Architecture. 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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  25. (1 other version)Agent-based modeling: the right mathematics for the social sciences?Paul 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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  26. Is Evolution Algorithmic?Marcin Miłkowski - 2009 - Minds and Machines 19 (4):465-475.
    In Darwin’s Dangerous Idea, Daniel Dennett claims that evolution is algorithmic. On Dennett’s analysis, evolutionary processes are trivially algorithmic because he assumes that all natural processes are algorithmic. I will argue that there are more robust ways to understand algorithmic processes that make the claim that evolution is algorithmic empirical and not conceptual. While laws of nature can be seen as compression algorithms of information about the world, it does not follow logically that they are implemented as algorithms by physical (...)
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  27. Effective Physical Processes and Active Information in Quantum Computing.Ignazio Licata - 2007 - Quantum Biosystems 1 (1):51-65.
    The recent debate on hypercomputation has raised new questions both on the computational abilities of quantum systems and the Church-Turing Thesis role in Physics.We propose here the idea of “effective physical process” as the essentially physical notion of computation. By using the Bohm and Hiley active information concept we analyze the differences between the standard form (quantum gates) and the non-standard one (adiabatic and morphogenetic) of Quantum Computing, and we point out how its Super-Turing potentialities derive from an incomputable information (...)
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  28. Three concepts of decidability for general subsets of uncountable spaces.Matthew W. Parker - 2003 - Theoretical Computer Science 351 (1):2-13.
    There is no uniquely standard concept of an effectively decidable set of real numbers or real n-tuples. Here we consider three notions: decidability up to measure zero [M.W. Parker, Undecidability in Rn: Riddled basins, the KAM tori, and the stability of the solar system, Phil. Sci. 70(2) (2003) 359–382], which we abbreviate d.m.z.; recursive approximability [or r.a.; K.-I. Ko, Complexity Theory of Real Functions, Birkhäuser, Boston, 1991]; and decidability ignoring boundaries [d.i.b.; W.C. Myrvold, The decision problem for entanglement, in: R.S. (...)
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  29. Supermachines and superminds.Eric Steinhart - 2003 - Minds and Machines 13 (1):155-186.
    If the computational theory of mind is right, then minds are realized by machines. There is an ordered complexity hierarchy of machines. Some finite machines realize finitely complex minds; some Turing machines realize potentially infinitely complex minds. There are many logically possible machines whose powers exceed the Church–Turing limit (e.g. accelerating Turing machines). Some of these supermachines realize superminds. Superminds perform cognitive supertasks. Their thoughts are formed in infinitary languages. They perceive and manipulate the infinite detail of fractal objects. They (...)
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  30. Searle, Syntax, and Observer Relativity.Ronald P. Endicott - 1996 - Canadian Journal of Philosophy 26 (1):101-22.
    I critically examine some provocative arguments that John Searle presents in his book The Rediscovery of Mind to support the claim that the syntactic states of a classical computational system are "observer relative" or "mind dependent" or otherwise less than fully and objectively real. I begin by explaining how this claim differs from Searle's earlier and more well-known claim that the physical states of a machine, including the syntactic states, are insufficient to determine its semantics. In contrast, his more recent (...)
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  31. Time phases, pointers, rules and embedding.John A. Barnden - 1993 - Behavioral and Brain Sciences 16 (3):451-452.
    This paper is a commentary on the target article by Lokendra Shastri & Venkat Ajjanagadde [S&A]: “From simple associations to systematic reasoning: A connectionist representation of rules, variables and dynamic bindings using temporal synchrony” in same issue of the journal, pp.417–451. -/- It puts S&A's temporal-synchrony binding method in a broader context, comments on notions of pointing and other ways of associating information - in both computers and connectionist systems - and mentions types of reasoning that are a challenge to (...)
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  32. Architectures of Intelligent Systems.David Kirsh - 1992 - Exploring Brain Functions:293-321.
    Theories of intelligence can be of use to neuroscientists if they: 1. Provide illuminating suggestions about the functional architecture of neural systems; 2. Suggest specific models of processing that neural circuits might implement. The objective of our session was to stand back and consider the prospects for this interdisciplinary exchange.
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  33. The centrality of instantiations.John A. Barnden - 1987 - Behavioral and Brain Sciences 10 (3):437-438.
    This paper is a commentary on the target article by Michael Arbib, “Levels of modeling of mechanisms of visually guided behavior”, in the same issue of the journal, pp. 407–465. -/- I focus on the importance of the inclusion of an ability of a system to entertain, at a given time, multiple instantiations of a given schema (situation template, frame, script, action plan, etc.), and complications introduced into neural/connectionist network systems by such inclusion.
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  34. Connectionist value units: Some concerns.John A. Barnden - 1986 - Behavioral and Brain Sciences 9 (1):92-93.
    This paper is a commentary on the target article by Dana H. Ballard, “Cortical connections and parallel processing: Structure and function”, in the same issue of the journal, pp. 67–120. -/- I raise some issues about the connectionist or neural-network implementation of information and information processing. Issues include the sharing of information by different parts of a connectionist/neural network, the copying of complex information from one place to another in a network, the possibility of connection weights not being synaptic weights, (...)
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  35. P≠NP, By accepting to make a shift in the Theory (Time as a fuzzy concept) The Structure of a Theory (TC*, Theory of Computation based on Fuzzy time).Farzad Didehvar - manuscript
    In a series of articles we try to show the need of a novel Theory for Theory of Computation based on considering time as a Fuzzy concept. Time is a central concept In Physics. First we were forced to consider some changes and modifications in the Theories of Physics. In the second step and throughout this article we show the positive Impact of this modification on Theory of Computation and Complexity Theory to rebuild it in a more successful and fruitful (...)
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  36. (1 other version)How Downwards Causation Occurs in Digital Computers.George Ellis - manuscript
    Digital computers carry out algorithms coded in high level programs. These abstract entities determine what happens at the physical level: they control whether electrons flow through specific transistors at specific times or not, entailing downward causation in both the logical and implementation hierarchies. This paper explores how this is possible in the light of the alleged causal completeness of physics at the bottom level, and highlights the mechanism that enables strong emergence (the manifest causal effectiveness of application programs) to occur. (...)
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  37. On the impossibility of using analogue machines to calculate non-computable functions.Robin O. Gandy - manuscript - Translated by Aran Nayebi.
    A number of examples have been given of physical systems (both classical and quantum mechanical) which when provided with a (continuously variable) computable input will give a non-computable output. It has been suggested that these systems might allow one to design analogue machines which would calculate the values of some number-theoretic non-computable function. Analysis of the examples show that the suggestion is wrong. In Section 4 I claim that given a reasonable definition of analogue machine it will always be wrong. (...)
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