Results for 'Morphological computation'

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  1. What is Morphological Computation? On How the Body Contributes to Cognition and Control.Vincent C. Müller & Matej Hoffmann - 2017 - Artificial Life 23 (1):1-24.
    The contribution of the body to cognition and control in natural and artificial agents is increasingly described as “off-loading computation from the brain to the body”, where the body is said to perform “morphological computation”. Our investigation of four characteristic cases of morphological computation in animals and robots shows that the ‘off-loading’ perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word. We (...)
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  2.  45
    Radical Embodiment and Morphological Computation: Against the Autonomy of (Some) Special Sciences.Paco Calvo & John Symons - unknown
    An asymmetry between the demands at the computational and algorithmic levels of description furnishes the illusion that the abstract profile at the computational level can be multiply realized, and that something is actually being shared at the algorithmic one. A disembodied rendering of the situation lays the stress upon the different ways in which an algorithm can be implemented. However, from an embodied approach, things look rather different. The relevant pairing, I shall argue, is not between implementation and algorithm, but (...)
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  3. Nature as a Network of Morphological Infocomputational Processes for Cognitive Agents.Gordana Dodig Crnkovic - 2017 - Eur. Phys. J. Special Topics 226 (2):181-195.
    This paper presents a view of nature as a network of infocomputational agents organized in a dynamical hierarchy of levels. It provides a framework for unification of currently disparate understandings of natural, formal, technical, behavioral and social phenomena based on information as a structure, differences in one system that cause the differences in another system, and computation as its dynamics, i.e. physical process of morphological change in the informational structure. We address some of the frequent misunderstandings regarding the (...)
     
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  4. Simple or Complex Bodies? Trade-Offs in Exploiting Body Morphology for Control.Matej Hoffmann & Vincent C. Müller - 2017 - In Gordana Dodig-Crnkovic & Raffaela Giovagnoli (eds.), Representation of Reality: Humans, Other Living Organisms and Intelligent Machines. Berlin: Springer. pp. 335-345.
    Engineers fine-tune the design of robot bodies for control purposes, however, a methodology or set of tools is largely absent, and optimization of morphology (shape, material properties of robot bodies, etc.) is lagging behind the development of controllers. This has become even more prominent with the advent of compliant, deformable or ”soft” bodies. These carry substantial potential regarding their exploitation for control—sometimes referred to as ”morphological computation”. In this article, we briefly review different notions of computation by (...)
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  5. 20 Years After The Embodied Mind - Why is Cognitivism Alive and Kicking?Vincent C. Müller - 2013 - In Blay Whitby & Joel Parthmore (eds.), Re-Conceptualizing Mental "Illness": The View from Enactivist Philosophy and Cognitive Science - AISB Convention 2013. AISB. pp. 47-49.
    I want to suggest that the major influence of classical arguments for embodiment like "The Embodied Mind" by Varela, Thomson & Rosch (1991) has been a changing of positions rather than a refutation: Cognitivism has found ways to retreat and regroup at positions that have better fortification, especially when it concerns theses about artificial intelligence or artificial cognitive systems. For example: a) Agent-based cognitivism' that understands humans as taking in representations of the world, doing rule-based processing and then acting on (...)
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  6.  2
    Reality Construction in Cognitive Agents Through Processes of Info-Computation.Gordana Dodig Crnkovic & Rickard von Haugwitz - forthcoming - In Gordana Dodge Crnkovic & Rafaela Giovagnoli (eds.), Representation and Reality in Humans, Animals and Machines. Heidelberg: Springer.
    Some intriguing questions such as: What is reality for an agent? How does reality of a bacterium differ from a reality of a human brain? Do we need representation in order to understand reality? are still widely debated. Starting with the presentation of the computing nature as an info-computational framework, where information is defined as a structure, and computation as information processing, we address questions of evolution of increasingly complex living agents through interactions with the environment. In this context, (...)
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  7.  20
    Alan Turing's Legacy: Info-Computational Philosophy of Nature.Gordana Dodig-Crnkovic - 2013 - In Gordana Dodig-Crnkovic Raffaela Giovagnoli (ed.), Computing Nature. Heidelberg: Springer. pp. 115--123.
    Alan Turing’s pioneering work on computability, and his ideas on morphological computing support Andrew Hodges’ view of Turing as a natural philosopher. Turing’s natural philosophy differs importantly from Galileo’s view that the book of nature is written in the language of mathematics (The Assayer, 1623). Computing is more than a language used to describe nature as computation produces real time physical behaviors. This article presents the framework of Natural info-computationalism as a contemporary natural philosophy that builds on the (...)
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  8. The Cognitive Basis of Computation: Putting Computation in Its Place.Daniel D. Hutto, Erik Myin, Anco Peeters & Farid Zahnoun - 2018 - In Mark Sprevak & Matteo Colombo (eds.), The Routledge Handbook of the Computational Mind. London: Routledge. pp. 272-282.
    The mainstream view in cognitive science is that computation lies at the basis of and explains cognition. Our analysis reveals that there is no compelling evidence or argument for thinking that brains compute. It makes the case for inverting the explanatory order proposed by the computational basis of cognition thesis. We give reasons to reverse the polarity of standard thinking on this topic, and ask how it is possible that computation, natural and artificial, might be based on cognition (...)
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  9.  74
    A Cognitive Computation Fallacy? Cognition, Computations and Panpsychism.John Mark Bishop - 2009 - Cognitive Computation 1 (3):221-233.
    The journal of Cognitive Computation is defined in part by the notion that biologically inspired computational accounts are at the heart of cognitive processes in both natural and artificial systems. Many studies of various important aspects of cognition (memory, observational learning, decision making, reward prediction learning, attention control, etc.) have been made by modelling the various experimental results using ever-more sophisticated computer programs. In this manner progressive inroads have been made into gaining a better understanding of the many components (...)
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  10. Neural Computation and the Computational Theory of Cognition.Gualtiero Piccinini & Sonya Bahar - 2013 - Cognitive Science 37 (3):453-488.
    We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism—neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation (...)
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  11. Information Processing, Computation, and Cognition.Gualtiero Piccinini & Andrea Scarantino - 2011 - Journal of Biological Physics 37 (1):1-38.
    Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are (...)
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  12. Computation Vs. Information Processing: Why Their Difference Matters to Cognitive Science.Gualtiero Piccinini & Andrea Scarantino - 2010 - Studies in History and Philosophy of Science Part A 41 (3):237-246.
    Since the cognitive revolution, it has become commonplace that cognition involves both computation and information processing. Is this one claim or two? Is computation the same as information processing? The two terms are often used interchangeably, but this usage masks important differences. In this paper, we distinguish information processing from computation and examine some of their mutual relations, shedding light on the role each can play in a theory of cognition. We recommend that theorists of cognition be (...)
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  13.  17
    Cognitive Computation Sans Representation.Paul Schweizer - 2017 - In Thomas M. 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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  14. What is Computation?B. Jack Copeland - 1996 - Synthese 108 (3):335-59.
    To compute is to execute an algorithm. More precisely, to say that a device or organ computes is to say that there exists a modelling relationship of a certain kind between it and a formal specification of an algorithm and supporting architecture. The key issue is to delimit the phrase of a certain kind. I call this the problem of distinguishing between standard and nonstandard models of computation. The successful drawing of this distinction guards Turing's 1936 analysis of (...) against a difficulty that has persistently been raised against it, and undercuts various objections that have been made to the computational theory of mind. (shrink)
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  15. Information Theory, Evolutionary Computation, and Dembski's "Complex Specified Information".Wesley Elsberry & Jeffrey Shallit - 2011 - Synthese 178 (2):237 - 270.
    Intelligent design advocate William Dembski has introduced a measure of information called "complex specified information", or CSI. He claims that CSI is a reliable marker of design by intelligent agents. He puts forth a "Law of Conservation of Information" which states that chance and natural laws are incapable of generating CSI. In particular, CSI cannot be generated by evolutionary computation. Dembski asserts that CSI is present in intelligent causes and in the flagellum of Escherichia coli, and concludes that neither (...)
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  16. Beyond Formal Structure: A Mechanistic Perspective on Computation and Implementation.Marcin Miłkowski - 2011 - Journal of Cognitive Science 12 (4):359-379.
    In this article, after presenting the basic idea of causal accounts of implementation and the problems they are supposed to solve, I sketch the model of computation preferred by Chalmers and argue that it is too limited to do full justice to computational theories in cognitive science. I also argue that it does not suffice to replace Chalmers’ favorite model with a better abstract model of computation; it is necessary to acknowledge the causal structure of physical computers that (...)
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  17. Explaining Computation Without Semantics: Keeping It Simple. [REVIEW]Nir Fresco - 2010 - Minds and Machines 20 (2):165-181.
    This paper deals with the question: how is computation best individuated? -/- 1. The semantic view of computation: computation is best individuated by its semantic properties. 2. The causal view of computation: computation is best individuated by its causal properties. 3. The functional view of computation: computation is best individuated by its functional properties. -/- Some scientific theories explain the capacities of brains by appealing to computations that they supposedly perform. The reason for (...)
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  18.  19
    A Simplicity Criterion for Physical Computation.Tyler Millhouse - forthcoming - British Journal for the Philosophy of Science:axx046.
    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 (...)
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  19.  79
    The Explanatory Role of Computation in Cognitive Science.Nir Fresco - 2012 - Minds and Machines 22 (4):353-380.
    Which notion of computation (if any) is essential for explaining cognition? Five answers to this question are discussed in the paper. (1) The classicist answer: symbolic (digital) computation is required for explaining cognition; (2) The broad digital computationalist answer: digital computation broadly construed is required for explaining cognition; (3) The connectionist answer: sub-symbolic computation is required for explaining cognition; (4) The computational neuroscientist answer: neural computation (that, strictly, is neither digital nor analogue) is required for (...)
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  20.  55
    The Epistemic Relevance of Morphological Content.Terry Horgan & Matjaž Potrč - 2010 - Acta Analytica 25 (2):155-173.
    Morphological content is information that is implicitly embodied in the standing structure of a cognitive system and is automatically accommodated during cognitive processing without first becoming explicit in consciousness. We maintain that much belief-formation in human cognition is essentially morphological : i.e., it draws heavily on large amounts of morphological content, and must do so in order to tractably accommodate the holistic evidential relevance of background information possessed by the cognitive agent. We also advocate a form of (...)
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  21.  73
    Physical Computation: A Mechanistic Account. [REVIEW]Joe Dewhurst - 2016 - Philosophical Psychology 29 (5):795-797.
    Physical Computation is the summation of Piccinini’s work on computation and mechanistic explanation over the past decade. It draws together material from papers published during that time, but also provides additional clarifications and restructuring that make this the definitive presentation of his mechanistic account of physical computation. This review will first give a brief summary of the account that Piccinini defends, followed by a chapter-by-chapter overview of the book, before finally discussing one aspect of the account in (...)
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  22. On Implementing a Computation.David J. Chalmers - 1994 - Minds and Machines 4 (4):391-402.
    To clarify the notion of computation and its role in cognitive science, we need an account of implementation, the nexus between abstract computations and physical systems. I provide such an account, based on the idea that a physical system implements a computation if the causal structure of the system mirrors the formal structure of the computation. The account is developed for the class of combinatorial-state automata, but is sufficiently general to cover all other discrete computational formalisms. The (...)
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  23.  61
    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 (...)
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  24.  44
    Information Processing as an Account of Concrete Digital Computation.Nir Fresco - 2013 - Philosophy and Technology 26 (1):31-60.
    It is common in cognitive science to equate computation (and in particular digital computation) with information processing. Yet, it is hard to find a comprehensive explicit account of concrete digital computation in information processing terms. An information processing account seems like a natural candidate to explain digital computation. But when ‘information’ comes under scrutiny, this account becomes a less obvious candidate. Four interpretations of information are examined here as the basis for an information processing account of (...)
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  25.  77
    Significance of Models of Computation, From Turing Model to Natural Computation.Gordana Dodig-Crnkovic - 2011 - Minds and Machines 21 (2):301-322.
    The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and (...)
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  26.  81
    Why Everything Doesn't Realize Every Computation.Ronald L. Chrisley - 1994 - Minds and Machines 4 (4):403-20.
    Some have suggested that there is no fact to the matter as to whether or not a particular physical system relaizes a particular computational description. This suggestion has been taken to imply that computational states are not real, and cannot, for example, provide a foundation for the cognitive sciences. In particular, Putnam has argued that every ordinary open physical system realizes every abstract finite automaton, implying that the fact that a particular computational characterization applies to a physical system does not (...)
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  27. Physical Computation: How General Are Gandy's Principles for Mechanisms?B. Jack Copeland & Oron Shagrir - 2007 - Minds and Machines 17 (2):217-231.
    What are the limits of physical computation? In his ‘Church’s Thesis and Principles for Mechanisms’, Turing’s student Robin Gandy proved that any machine satisfying four idealised physical ‘principles’ is equivalent to some Turing machine. Gandy’s four principles in effect define a class of computing machines (‘Gandy machines’). Our question is: What is the relationship of this class to the class of all (ideal) physical computing machines? Gandy himself suggests that the relationship is identity. We do not share this view. (...)
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  28.  65
    Effective Computation by Humans and Machines.Shagrir Oron - 2002 - Minds and Machines 12 (2):221-240.
    There is an intensive discussion nowadays about the meaning of effective computability, with implications to the status and provability of the Church–Turing Thesis (CTT). I begin by reviewing what has become the dominant account of the way Turing and Church viewed, in 1936, effective computability. According to this account, to which I refer as the Gandy–Sieg account, Turing and Church aimed to characterize the functions that can be computed by a human computer. In addition, Turing provided a highly convincing argument (...)
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  29.  90
    Information, Computation, Cognition. Agency-Based Hierarchies of Levels.Gordana Dodig Crnkovic - 2016 - In Vincent Müller (ed.), Fundamental Issues of Artificial Intelligence. Zurich: Springer. pp. 139-159.
    This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is needed (...)
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  30. Susan Stuart & Gordana Dodig Crnkovic : 'Computation, Information, Cognition: The Nexus and the Liminal'. [REVIEW]Vincent C. Müller - 2009 - Cybernetics and Human Knowing 16 (3-4):201-203.
    Review of: "Computation, Information, Cognition: The Nexus and the Liminal", Ed. Susan Stuart & Gordana Dodig Crnkovic, Newcastle: Cambridge Scholars Publishing, September 2007, xxiv+340pp, ISBN: 9781847180902, Hardback: £39.99, $79.99 ---- Are you a computer? Is your cat a computer? A single biological cell in your stomach, perhaps? And your desk? You do not think so? Well, the authors of this book suggest that you think again. They propose a computational turn, a turn towards computational explanation and towards the explanation (...)
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  31.  34
    The False Dichotomy Between Causal Realization and Semantic Computation.Marcin Miłkowski - 2017 - Hybris. Internetowy Magazyn Filozoficzny 38:1-21.
    In this paper, I show how semantic factors constrain the understanding of the computational phenomena to be explained so that they help build better mechanistic models. In particular, understanding what cognitive systems may refer to is important in building better models of cognitive processes. For that purpose, a recent study of some phenomena in rats that are capable of ‘entertaining’ future paths (Pfeiffer and Foster 2013) is analyzed. The case shows that the mechanistic account of physical computation may be (...)
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  32.  24
    In Search of Common Foundations for Cortical Computation.William A. Phillips & Wolf Singer - 1997 - Behavioral and Brain Sciences 20 (4):657-683.
    It is worthwhile to search for forms of coding, processing, and learning common to various cortical regions and cognitive functions. Local cortical processors may coordinate their activity by maximizing the transmission of information coherently related to the context in which it occurs, thus forming synchronized population codes. This coordination involves contextual field (CF) connections that link processors within and between cortical regions. The effects of CF connections are distinguished from those mediating receptive field (RF) input; it is shown how CFs (...)
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  33.  53
    How Molecules Matter to Mental Computation.Paul Thagard - 2002 - Philosophy of Science 69 (3):497-518.
    Almost all computational models of the mind and brain ignore details about neurotransmitters, hormones, and other molecules. The neglect of neurochemistry in cognitive science would be appropriate if the computational properties of brains relevant to explaining mental functioning were in fact electrical rather than chemical. But there is considerable evidence that chemical complexity really does matter to brain computation, including the role of proteins in intracellular computation, the operations of synapses and neurotransmitters, and the effects of neuromodulators such (...)
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  34.  28
    Objective Computation Versus Subjective Computation.Nir Fresco - 2015 - Erkenntnis 80 (5):1031-1053.
    The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely (...)
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  35.  57
    Concrete Digital Computation: What Does It Take for a Physical System to Compute? [REVIEW]Nir Fresco - 2011 - Journal of Logic, Language and Information 20 (4):513-537.
    This paper deals with the question: what are the key requirements for a physical system to perform digital computation? Time and again cognitive scientists are quick to employ the notion of computation simpliciter when asserting basically that cognitive activities are computational. They employ this notion as if there was or is a consensus on just what it takes for a physical system to perform computation, and in particular digital computation. Some cognitive scientists in referring to digital (...)
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  36. Two Concepts of "Form" and the so-Called Computational Theory of Mind.John-Michael M. Kuczynski - 2006 - Philosophical Psychology 19 (6):795-821.
    According to the computational theory of mind , to think is to compute. But what is meant by the word 'compute'? The generally given answer is this: Every case of computing is a case of manipulating symbols, but not vice versa - a manipulation of symbols must be driven exclusively by the formal properties of those symbols if it is qualify as a computation. In this paper, I will present the following argument. Words like 'form' and 'formal' are ambiguous, (...)
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  37.  55
    An Analysis of the Criteria for Evaluating Adequate Theories of Computation.Nir Fresco - 2008 - Minds and Machines 18 (3):379-401.
    This paper deals with the question: What are the criteria that an adequate theory of computation has to meet? 1. Smith's answer: it has to meet the empirical criterion (i.e. doing justice to computational practice), the conceptual criterion (i.e. explaining all the underlying concepts) and the cognitive criterion (i.e. providing solid grounds for computationalism). 2. Piccinini's answer: it has to meet the objectivity criterion (i.e. identifying computation as a matter of fact), the explanation criterion (i.e. explaining the computer's (...)
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  38.  37
    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, (...)
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  39.  11
    Socio-Technical Computation.Markus Luczak-Roesch, Ramine Tinati, Kieron O'Hara & Nigel Shadbolt - 2015 - In Proceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing.
    Motivated by the significant amount of successful collaborative problem solving activity on the Web, we ask: Can the accumulated information propagation behavior on the Web be conceived as a giant machine, and reasoned about accordingly? In this paper we elaborate a thesis about the computational capability embodied in information sharing activities that happen on the Web, which we term socio-technical computation, reflecting not only explicitly conditional activities but also the organic potential residing in information on the Web.
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  40.  83
    Computational Mechanisms and Models of Computation.Marcin Miłkowski - 2014 - Philosophia Scientae 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 variation (...)
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  41.  36
    What Is Nature-Like Computation? A Behavioural Approach and a Notion of Programmability.Hector Zenil - 2013 - Philosophy and Technology (3):1-23.
    The aim of this paper is to propose an alternative behavioural definition of computation (and of a computer) based simply on whether a system is capable of reacting to the environment—the input—as reflected in a measure of programmability. This definition is intended to have relevance beyond the realm of digital computers, particularly vis-à-vis natural systems. This will be done by using an extension of a phase transition coefficient previously defined in an attempt to characterise the dynamical behaviour of cellular (...)
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  42. Cognition is Not Computation: The Argument From Irreversibility.Selmer Bringsjord - 1997 - Synthese 113 (2):285-320.
    The dominant scientific and philosophical view of the mind – according to which, put starkly, cognition is computation – is refuted herein, via specification and defense of the following new argument: Computation is reversible; cognition isn't; ergo, cognition isn't computation. After presenting a sustained dialectic arising from this defense, we conclude with a brief preview of the view we would put in place of the cognition-is-computation doctrine.
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  43. Information and Computation: Essays on Scientific and Philosophical Understanding of Foundations of Information and Computation.Gordana Dodig Crnkovic & Mark Burgin (eds.) - 2011 - World Scientific.
    Information is a basic structure of the world, while computation is a process of the dynamic change of information. This book provides a cutting-edge view of world's leading authorities in fields where information and computation play a central role. It sketches the contours of the future landscape for the development of our understanding of information and computation, their mutual relationship and the role in cognition, informatics, biology, artificial intelligence, and information technology. -/- This book is an utterly (...)
  44.  38
    Temporal Logics with Reference Pointers and Computation Tree Logics.Valentin Goranko - 2000 - Journal of Applied Non-Classical Logics 10 (3):221-242.
    A complete axiomatic system CTL$_{rp}$ is introduced for a temporal logic for finitely branching $\omega^+$-trees in a temporal language extended with so called reference pointers. Syntactic and semantic interpretations are constructed for the branching time computation tree logic CTL$^{*}$ into CTL$_{rp}$. In particular, that yields a complete axiomatization for the translations of all valid CTL$^{*}$-formulae. Thus, the temporal logic with reference pointers is brought forward as a simpler (with no path quantifiers), but in a way more expressive medium for (...)
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  45.  85
    Computation is Just Interpretable Symbol Manipulation; Cognition Isn't.Stevan Harnad - 1994 - Minds and Machines 4 (4):379-90.
    Computation is interpretable symbol manipulation. Symbols are objects that are manipulated on the basis of rules operating only on theirshapes, which are arbitrary in relation to what they can be interpreted as meaning. Even if one accepts the Church/Turing Thesis that computation is unique, universal and very near omnipotent, not everything is a computer, because not everything can be given a systematic interpretation; and certainly everything can''t be givenevery systematic interpretation. But even after computers and computation have (...)
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  46. How Much of One-Way Computation Is Just Thermodynamics?Janet Anders, Michal Hajdušek, Damian Markham & Vlatko Vedral - 2008 - Foundations of Physics 38 (6):506-522.
    In this paper we argue that one-way quantum computation can be seen as a form of phase transition with the available information about the solution of the computation being the order parameter. We draw a number of striking analogies between standard thermodynamical quantities such as energy, temperature, work, and corresponding computational quantities such as the amount of entanglement, time, potential capacity for computation, respectively. Aside from being intuitively pleasing, this picture allows us to make novel conjectures, such (...)
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  47.  92
    Symbols and Computation: A Critique of the Computational Theory of Mind.Steven Horst - 1999 - Minds and Machines 9 (3):347-381.
    Over the past several decades, the philosophical community has witnessed the emergence of an important new paradigm for understanding the mind.1 The paradigm is that of machine computation, and its influence has been felt not only in philosophy, but also in all of the empirical disciplines devoted to the study of cognition. Of the several strategies for applying the resources provided by computer and cognitive science to the philosophy of mind, the one that has gained the most attention from (...)
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  48.  23
    Information and Computation Nets. Investigations Into Info-Computational World.Gordana Dodig-Crnkovic - 2009 - Vdm.
    The book presents investigations into the world of info-computational nature, in which information constitutes the structure, while computational process amounts to its change. Information and computation are inextricably bound: There is no computation without informational structure, and there is no information without computational process. Those two complementary ideas are used to build a conceptual net, which according to Novalis is a theoretical way of capturing reality. We apprehend the reality within a framework known as natural computationalism, the view (...)
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    Measurement-Based Quantum Computation and Undecidable Logic.Maarten Van den Nest & Hans J. Briegel - 2008 - Foundations of Physics 38 (5):448-457.
    We establish a connection between measurement-based quantum computation and the field of mathematical logic. We show that the computational power of an important class of quantum states called graph states, representing resources for measurement-based quantum computation, is reflected in the expressive power of (classical) formal logic languages defined on the underlying mathematical graphs. In particular, we show that for all graph state resources which can yield a computational speed-up with respect to classical computation, the underlying graphs—describing the (...)
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    In Computation, Parallel is Nothing, Physical Everything.Selmer Bringsjord - 2001 - Minds and Machines 11 (1):95-99.
    Andrew Boucher (1997) argues that ``parallel computation is fundamentally different from sequential computation'' (p. 543), and that this fact provides reason to be skeptical about whether AI can produce a genuinely intelligent machine. But parallelism, as I prove herein, is irrelevant. What Boucher has inadvertently glimpsed is one small part of a mathematical tapestry portraying the simple but undeniable fact that physical computation can be fundamentally different from ordinary, ``textbook'' computation (whether parallel or sequential). This tapestry (...)
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