Results for 'Computation and Representation'

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  1. Computation without representation.Gualtiero Piccinini - 2004 - Philosophical Studies 137 (2):205-241.
    The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...)
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  2.  25
    Computable Riesz representation for the dual of C [0; 1].Hong Lu & Klaus Weihrauch - 2007 - Mathematical Logic Quarterly 53 (4):415-430.
    By the Riesz representation theorem for the dual of C [0; 1], if F: C [0; 1] → ℝ is a continuous linear operator, then there is a function g: [0;1] → ℝ of bounded variation such that F = ∫ f dg . The function g can be normalized such that V = ‖F ‖. In this paper we prove a computable version of this theorem. We use the framework of TTE, the representation approach to computable analysis, (...)
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    Computation without Representation.Gualtiero Piccinini - 2008 - Philosophical Studies 137 (2):205-241.
    The received view is that computational states are individuated at least in part by their semantic properties. I offer an alternative, according to which computational states are individuated by their functional properties. Functional properties are specified by a mechanistic explanation without appealing to any semantic properties. The primary purpose of this paper is to formulate the alternative view of computational individuation, point out that it supports a robust notion of computational explanation, and defend it on the grounds of how computational (...)
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  4.  36
    Computation without representation.Stephen P. Stich - 1980 - Behavioral and Brain Sciences 3 (1):152-152.
  5. Cognitive Computation sans Representation.Paul Schweizer - 2017 - In Thomas M. Powers, Philosophy and Computing: Essays in epistemology, philosophy of mind, logic, and ethics. Cham: 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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  6.  15
    Computation without Representation: Nonsymbolic-Analog Processing.M. Gams - 1997 - In Matjaz Gams, Mind Versus Computer: Were Dreyfus and Winograd Right? Amsterdam: IOS Press. pp. 43--171.
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  7. Conscious Representations: An Intractable Problem for the Computational Theory of Mind.Bartlomiej Swiatczak - 2011 - Minds and Machines 21 (1):19-32.
    Advocates of the computational theory of mind claim that the mind is a computer whose operations can be implemented by various computational systems. According to these philosophers, the mind is multiply realisable because—as they claim—thinking involves the manipulation of syntactically structured mental representations. Since syntactically structured representations can be made of different kinds of material while performing the same calculation, mental processes can also be implemented by different kinds of material. From this perspective, consciousness plays a minor role in mental (...)
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  8. A computational neural theory of multisensory spatial representations.Alexandre Pouget, Sophie Deneve & Duhamel & Jean-Rene - 2004 - In Charles Spence & Jon Driver, Crossmodal Space and Crossmodal Attention. Oxford University Press.
  9. 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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  10. The Representational Foundations of Computation.Michael Rescorla - 2015 - Philosophia Mathematica 23 (3):338-366.
    Turing computation over a non-linguistic domain presupposes a notation for the domain. Accordingly, computability theory studies notations for various non-linguistic domains. It illuminates how different ways of representing a domain support different finite mechanical procedures over that domain. Formal definitions and theorems yield a principled classification of notations based upon their computational properties. To understand computability theory, we must recognize that representation is a key target of mathematical inquiry. We must also recognize that computability theory is an intensional (...)
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  11.  53
    Why computation need not be traded only for internal representation.Robert S. Stufflebeam - 1997 - Behavioral and Brain Sciences 20 (1):80-81.
    Although Clark & Thornton's “trading spaces” hypothesis is supposed to require trading internal representation for computation, it is not used consistently in that fashion. Not only do some of the offered computation-saving strategies turn out to be nonrepresentational, others (e.g., cultural artifacts) are external representations. Hence, C&T's hypothesis is consistent with antirepresentationalism.
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  12. Computational Approaches to Concepts Representation: A Whirlwind Tour.Mattia Fumagalli, Riccardo Baratella, Marcello Frixione & Daniele Porello - forthcoming - Acta Analytica:1-32.
    The modelling of concepts, besides involving disciplines like philosophy of mind and psychology, is a fundamental and lively research problem in several artificial intelligence (AI) areas, such as knowledge representation, machine learning, and natural language processing. In this scenario, the most prominent proposed solutions adopt different (often incompatible) assumptions about the nature of such a notion. Each of these solutions has been developed to capture some specific features of concepts and support some specific (artificial) cognitive operations. This paper critically (...)
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  13. Motivational Representations within a Computational Cognitive Architecture.Ron Sun - unknown
    This paper discusses essential motivational representations necessary for a comprehensive computational cognitive architecture. It hypothesizes the need for implicit drive representations, as well as explicit goal representations. Drive representations consist of primary drives — both low-level primary drives (concerned mostly with basic physiological needs) and high-level primary drives (concerned more with social needs), as well as derived (secondary) drives. On the basis of drives, explicit goals may be generated on the fly during an agent’s interaction with various situations. These motivational (...)
     
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  14.  70
    The Computational Origin of Representation.Steven T. Piantadosi - 2020 - Minds and Machines 31 (1):1-58.
    Each of our theories of mental representation provides some insight into how the mind works. However, these insights often seem incompatible, as the debates between symbolic, dynamical, emergentist, sub-symbolic, and grounded approaches to cognition attest. Mental representations—whatever they are—must share many features with each of our theories of representation, and yet there are few hypotheses about how a synthesis could be possible. Here, I develop a theory of the underpinnings of symbolic cognition that shows how sub-symbolic dynamics may (...)
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  15.  42
    Argument Representation for Dependable Computer-Based Systems.C. Gurr - 2002 - Informal Logic 22 (3):293-321.
    Society is becoming increasingly reliant upon the dependability of computerbased systems. Achieving and demonstrating the dependability of systems requires the construction and review of valid and coherent arguments. This paper discusses the need for a variety of classes of arguments in dependable systems and reviews existing approaches to the representation of arguments in each of these classes. The issues surrounding the certification of safety critical systems demonstrate the current need for richer representations of dependability arguments which support tools for (...)
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  16. Why go for a computation-based approach to cognitive representation.Dimitri Coelho Mollo - 2021 - Synthese 199 (3-4):6875-6895.
    An influential view in cognitive science is that computation in cognitive systems is semantic, conceptually depending on representation: to compute is to manipulate representations. I argue that accepting the non-semantic teleomechanistic view of computation lays the ground for a promising alternative strategy, in which computation helps to explain and naturalise representation, rather than the other way around. I show that this computation-based approach to representation presents six decisive advantages over the semantic view. I (...)
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  17.  46
    Computers in Abstraction/Representation Theory.Samuel C. Fletcher - 2018 - Minds and Machines 28 (3):445-463.
    Recently, Horsman et al. have proposed a new framework, Abstraction/Representation theory, for understanding and evaluating claims about unconventional or non-standard computation. Among its attractive features, the theory in particular implies a novel account of what is means to be a computer. After expounding on this account, I compare it with other accounts of concrete computation, finding that it does not quite fit in the standard categorization: while it is most similar to some semantic accounts, it is not (...)
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  18. Computational Representation of Practical Argument.Katie Atkinson, Trevor Bench-Capon & Peter McBurney - 2006 - Synthese 152 (2):157-206.
    In this paper we consider persuasion in the context of practical reasoning, and discuss the problems associated with construing reasoning about actions in a manner similar to reasoning about beliefs. We propose a perspective on practical reasoning as presumptive justification of a course of action, along with critical questions of this justification, building on the account of Walton. From this perspective, we articulate an interaction protocol, which we call PARMA, for dialogues over proposed actions based on this theory. We outline (...)
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  19.  32
    Lattice representations for computability theory.Peter A. Fejer - 1998 - Annals of Pure and Applied Logic 94 (1-3):53-74.
    Lattice representations are an important tool for computability theorists when they embed nondistributive lattices into degree-theoretic structures. In this expository paper, we present the basic definitions and results about lattice representations needed by computability theorists. We define lattice representations both from the lattice-theoretic and computability-theoretic points of view, give examples and show the connection between the two types of representations, discuss some of the known theorems on the existence of lattice representations that are of interest to computability theorists, and give (...)
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  20.  38
    Computations over abstract categories of representation.Roy Eagleson - 1990 - Behavioral and Brain Sciences 13 (4):661-662.
  21.  63
    Informational Equivalence but Computational Differences? Herbert Simon on Representations in Scientific Practice.David Waszek - 2024 - Minds and Machines 34 (1):93-116.
    To explain why, in scientific problem solving, a diagram can be “worth ten thousand words,” Jill Larkin and Herbert Simon (1987) relied on a computer model: two representations can be “informationally” equivalent but differ “computationally,” just as the same data can be encoded in a computer in multiple ways, more or less suited to different kinds of processing. The roots of this proposal lay in cognitive psychology, more precisely in the “imagery debate” of the 1970s on whether there are image-like (...)
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  22. A computational neural theory of multisensory spatial representations.A. Pouget, S. Deneve & J. R. Duhamel - 2004 - In Charles Spence & Jon Driver, Crossmodal Space and Crossmodal Attention. Oxford University Press. pp. 123--140.
  23.  50
    Computable irrational numbers with representations of surprising complexity.Ivan Georgiev, Lars Kristiansen & Frank Stephan - 2021 - Annals of Pure and Applied Logic 172 (2):102893.
  24.  71
    The role of representation in computation.Gerard O'Brien & Jon Opie - 2009 - Cognitive Processing 10 (1):53-62.
    Reformers urge that representation no longer earns its explanatory keep in cognitive science, and that it is time to discard this troublesome concept. In contrast, we hold that without representation cognitive science is utterly bereft of tools for explaining natural intelligence. In order to defend the latter position, we focus on the explanatory role of representation in computation. We examine how the methods of digital and analog computation are used to model a relatively simple target (...)
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  25. Modelling Empty Representations: The Case of Computational Models of Hallucination.Marcin Miłkowski - 2017 - In Gordana Dodig-Crnkovic & Raffaela Giovagnoli, Representation of Reality: Humans, Other Living Organism and Intelligent Machines. Heidelberg: Springer. pp. 17--32.
    I argue that there are no plausible non-representational explanations of episodes of hallucination. To make the discussion more specific, I focus on visual hallucinations in Charles Bonnet syndrome. I claim that the character of such hallucinatory experiences cannot be explained away non-representationally, for they cannot be taken as simple failures of cognizing or as failures of contact with external reality—such failures being the only genuinely non-representational explanations of hallucinations and cognitive errors in general. I briefly introduce a recent computational model (...)
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  26.  42
    The computational/representational paradigm as normal science: further support.Steven W. Zucker - 1980 - Behavioral and Brain Sciences 3 (3):406-407.
  27.  64
    A computational representation for generalised phrase-structure grammars.John D. Phillips - 1992 - Linguistics and Philosophy 15 (3):255 - 287.
    Some modifications are suggested to recent (1985) generalised phrase-structure grammar which make the formalism more suitable to computational use, and at the same time provide a clear and elegant redefinition for parts of the formalism which are standardly complex and ill-defined. It is shown how the feature-instantiation principles can be represented as explicit rules in a format similar to metarules, and how a grammar of four parts, immediate-dominance rules, linear-precedence rules, metarules, and these new propagation rules, can be used to (...)
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  28. A computable von Neumann-Morgenstern representation theorem.Josiah Lopez-Wild - 2025 - Synthese 205 (5):1-25.
    Expected utility theory seeks to define rational choice behavior. Given a collection of acts available to some decision maker, expected utility theorists commonly identify the “rational” act as the act which _maximizes expected utility_ (where the expectation is taken with respect to some probability measure). The mathematical core of expected utility theory is a representation theorem. These theorems link expected utility maximization to a qualitative description of an agent’s choice behavior, captured in a preference relation. We say that an (...)
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  29.  49
    CaMeRa: A Computational Model of Multiple Representations.Hermina J. M. Tabachneck-Schijf, Anthony M. Leonardo & Herbert A. Simon - 1997 - Cognitive Science 21 (3):305-350.
    This research aims to clarify, by constructing and testing a computer simulation, the use of multiple representations in problem solving, focusing on their role in visual reasoning. The model is motivated by extensive experimental evidence in the literature for the features it incorporates, but this article focuses on the system's structure. We illustrate the model's behavior by simulating the cognitive and perceptual processes of an economics expert as he teaches some well‐learned economics principles while drawing a graph on a blackboard. (...)
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  30. The role of cognitive modeling for user interface design representations: An epistemological analysis of knowledge engineering in the context of human-computer interaction. [REVIEW]Markus F. Peschl & Chris Stary - 1998 - Minds and Machines 8 (2):203-236.
    In this paper we review some problems with traditional approaches for acquiring and representing knowledge in the context of developing user interfaces. Methodological implications for knowledge engineering and for human-computer interaction are studied. It turns out that in order to achieve the goal of developing human-oriented (in contrast to technology-oriented) human-computer interfaces developers have to develop sound knowledge of the structure and the representational dynamics of the cognitive system which is interacting with the computer.We show that in a first step (...)
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  31.  47
    Completing the Physical Representation of Quantum Algorithms Provides a Quantitative Explanation of Their Computational Speedup.Giuseppe Castagnoli - 2018 - Foundations of Physics 48 (3):333-354.
    The usual representation of quantum algorithms, limited to the process of solving the problem, is physically incomplete. We complete it in three steps: extending the representation to the process of setting the problem, relativizing the extended representation to the problem solver to whom the problem setting must be concealed, and symmetrizing the relativized representation for time reversal to represent the reversibility of the underlying physical process. The third steps projects the input state of the representation, (...)
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  32. Direct deductive computation on discourse representation structures.Uwe Reyle & Dov M. Gabbay - 1994 - Linguistics and Philosophy 17 (4):343 - 390.
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  33.  56
    Qualitative Models in Computational Simulative Sciences: Representation, Confirmation, Experimentation.Nicola Angius - 2019 - Minds and Machines 29 (3):397-416.
    The Epistemology Of Computer Simulation has developed as an epistemological and methodological analysis of simulative sciences using quantitative computational models to represent and predict empirical phenomena of interest. In this paper, Executable Cell Biology and Agent-Based Modelling are examined to show how one may take advantage of qualitative computational models to evaluate reachability properties of reactive systems. In contrast to the thesis, advanced by EOCS, that computational models are not adequate representations of the simulated empirical systems, it is shown how (...)
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  34.  45
    Modelling Empty Representations: The Case of Computational Models of Hallucination.Marcin Miłkowski - 2017 - In Gordana Dodig-Crnkovic & Raffaela Giovagnoli, Representation of Reality: Humans, Other Living Organism and Intelligent Machines. Heidelberg: Springer. pp. 17--32.
    I argue that there are no plausible non-representational explanations of episodes of hallucination. To make the discussion more specific, I focus on visual hallucinations in Charles Bonnet syndrome. I claim that the character of such hallucinatory experiences cannot be explained away non-representationally, for they cannot be taken as simple failures of cognizing or as failures of contact with external reality—such failures being the only genuinely non-representational explanations of hallucinations and cognitive errors in general. I briefly introduce a recent computational model (...)
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  35.  28
    Styles of computational representation.M. P. Smith - 1988 - Behavioral and Brain Sciences 11 (3):530.
  36.  21
    On the representational/computational properties of multiple memory systems.Russell A. Poldrack & Neal J. Cohen - 1994 - Behavioral and Brain Sciences 17 (3):416-417.
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  37.  64
    Building Cognition: The Construction of Computational Representations for Scientific Discovery.Sanjay Chandrasekharan & Nancy J. Nersessian - 2015 - Cognitive Science 39 (8):1727-1763.
    Novel computational representations, such as simulation models of complex systems and video games for scientific discovery, are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that (...)
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  38.  11
    Computational Logic — CL 2000: First International Conference London, UK, July 24–28, 2000 Proceedings.John Lloyd, Veronica Dahl, Ulrich Furbach, Manfred Kerber, Kung-Kiu Lau, Catuscia Palamidessi, Luis M. Pereira, Yehoshua Sagiv & Peter J. Stuckey - 2000 - Springer Verlag.
    These are the proceedings of the First International Conference on Compu- tional Logic (CL 2000) which was held at Imperial College in London from 24th to 28th July, 2000. The theme of the conference covered all aspects of the theory, implementation, and application of computational logic, where computational logic is to be understood broadly as the use of logic in computer science. The conference was collocated with the following events: { 6th International Conference on Rules and Objects in Databases (DOOD (...)
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  39. Computationalism: Still the Only Game in Town: A Reply to Swiatczak’s “Conscious Representations: An Intractable Problem for the Computational Theory of Mind”. [REVIEW]David Davenport - 2012 - Minds and Machines 22 (3):183-190.
    Abstract Mental representations, Swiatczak (Minds Mach 21:19–32, 2011) argues, are fundamentally biochemical and their operations depend on consciousness; hence the computational theory of mind, based as it is on multiple realisability and purely syntactic operations, must be wrong. Swiatczak, however, is mistaken. Computation, properly understood, can afford descriptions/explanations of any physical process, and since Swiatczak accepts that consciousness has a physical basis, his argument against computationalism must fail. Of course, we may not have much idea how consciousness (itself a (...)
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  40. The Machine Scenario: A Computational Perspective on Alternative Representations of Indeterminism.Vincent Grandjean & Matteo Pascucci - 2020 - Minds and Machines 31 (1):59-74.
    In philosophical logic and metaphysics there is a long-standing debate around the most appropriate structures to represent indeterministic scenarios concerning the future. We reconstruct here such a debate in a computational setting, focusing on the fundamental difference between moment-based and history-based structures. Our presentation is centered around two versions of an indeterministic scenario in which a programmer wants a machine to perform a given task at some point after a specified time. One of the two versions includes an assumption about (...)
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  41.  51
    Computation as the boundary of the cognitive.Daniel Weiskopf - 2024 - Mind and Language 39 (1):123-128.
    Khalidi identifies cognition with Marrian computation. He further argues that Marrian levels of inquiry should be interpreted ontologically as corresponding to distinct semi‐closed causal domains. But this counterintuitively places the causal domain of representations outside of cognition proper. A closer look at Khalidi's account of concepts shows that these allegedly separate Marrian domains are more tightly integrated than he allows. Theories of concepts converge on algorithmic‐representational models rather than computational ones. This suggests that we should reject the wholesale identification (...)
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  42.  58
    Physical Computation: A Mechanistic Account.Gualtiero Piccinini - 2015 - Oxford, GB: Oxford University Press UK.
    Gualtiero Piccinini articulates and defends a mechanistic account of concrete, or physical, computation. A physical system is a computing system just in case it is a mechanism one of whose functions is to manipulate vehicles based solely on differences between different portions of the vehicles according to a rule defined over the vehicles. Physical Computation discusses previous accounts of computation and argues that the mechanistic account is better. Many kinds of computation are explicated, such as digital (...)
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  43.  35
    Uncovering the Structure of Semantic Representations Using a Computational Model of Decision‐Making.Sonia Ramotowska, Shane Steinert-Threlkeld, Leendert van Maanen & Jakub Szymanik - 2023 - Cognitive Science 47 (1):e13234.
    According to logical theories of meaning, a meaning of an expression can be formalized and encoded in truth conditions. Vagueness of the language and individual differences between people are a challenge to incorporate into the meaning representations. In this paper, we propose a new approach to study truth-conditional representations of vague concepts. For a case study, we selected two natural language quantifiers most and more than half. We conducted two online experiments, each with 90 native English speakers. In the first (...)
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  44. Explaining computation without semantics: Keeping it simple.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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  45. A theory of computational implementation.Michael Rescorla - 2014 - Synthese 191 (6):1277-1307.
    I articulate and defend a new theory of what it is for a physical system to implement an abstract computational model. According to my descriptivist theory, a physical system implements a computational model just in case the model accurately describes the system. Specifically, the system must reliably transit between computational states in accord with mechanical instructions encoded by the model. I contrast my theory with an influential approach to computational implementation espoused by Chalmers, Putnam, and others. I deploy my theory (...)
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  46.  73
    Representation without symbol systems.Stephen M. Kosslyn & Gary Hatfield - 1984 - Social Research: An International Quarterly 51 (4):1019-1045.
    The concept of representation has become almost inextricably bound to the concept of symbol systems. the concepts is nowhere more prevalent than in descriptions of "internal representations." These representations are thought to occur in an internal symbol system that allows the brain to store and use information. In this paper we explore a different approach to understanding psychological processes, one that retains a commitment to representations and computations but that is not based on the idea that information must be (...)
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  47.  95
    Structural Representation as Complexity Management.Manolo Martínez - forthcoming - In Gualtiero Piccinini, Neurocognitive Foundations of Mind. Routledge.
    Cognition can often be modeled as the transformation of a set of variables into another. At least two kinds of entities are needed in this process: signals and coders. Representations are usually taken to be signals, but sometimes they are the coders: sometimes the computational complexity of variable transformations can be strikingly reduced by relying on a structure that mirrors that of some task-relevant entity. These kinds of coders are what philosophers call structural representations.
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  48.  20
    Computational complexity on computable metric spaces.Klaus Weirauch - 2003 - Mathematical Logic Quarterly 49 (1):3-21.
    We introduce a new Turing machine based concept of time complexity for functions on computable metric spaces. It generalizes the ordinary complexity of word functions and the complexity of real functions studied by Ko [19] et al. Although this definition of TIME as the maximum of a generally infinite family of numbers looks straightforward, at first glance, examples for which this maximum exists seem to be very rare. It is the main purpose of this paper to prove that, nevertheless, the (...)
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  49.  12
    A Computational Model of Wason's Selection Task.Emmanuel Genot - unknown
    We apply an algorithmic learning model of inquiry to model reasoning carried by experimental subjects in Wason's _Selection Task_ that represents reasoning in the task as computation of a decision tree that supervenes on semantic representations. We argue that the resulting model improves on previous probabilistic and pragmatic models of the task. In particular, it suggests that subjects' selection could in fact be guided by sophisticated patterns of argumentative reasoning.
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  50. 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 (...)
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