Results for 'Computation Language'

955 found
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  1.  53
    Computational language systems, architectures.Hamish Cunningham & Kalina Bontcheva - 2005 - In Keith Brown, Encyclopedia of Language and Linguistics. Elsevier. pp. 733--752.
  2.  32
    Computational Language Assessments of Harmony in Life — Not Satisfaction With Life or Rating Scales — Correlate With Cooperative Behaviors.Oscar Kjell, Daiva Daukantaitė & Sverker Sikström - 2021 - Frontiers in Psychology 12:601679.
    Different types of well-being are likely to be associated with different kinds of behaviors. The first objective of this study was, from a subjective well-being perspective, to examine whether harmony in life and satisfaction with life are related differently to cooperative behaviors depending on individuals’ social value orientation. The second objective was, from a methodological perspective, to examine whether language-based assessments calledcomputational language assessments(CLA), which enable respondents to answer with words that are analyzed using natural language processing, (...)
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  3. Mathematics, Computation, Language and Poetry: The Novalis Paradox.Paul Redding - 2014 - In Dalia Nassar, The Relevance of Romanticism: Essays on German Romantic Philosophy. New York: Oxford University Press. pp. 221-238.
    Recent scholarship has helped to demythologise the life and work of Georg Philipp Friedrich von Hardenberg who, as the poet “Novalis”, had come to instantiate the nineteenth-century’s stereotype of the romantic poet. Among Hardenberg’s interests that seem to sit uneasily with this literary persona were his interests in science and mathematics, and especially in the idea, traceable back to Leibniz, of a mathematically based computational approach to language. Hardenberg’s approach to language, and his attempts to bring mathematics to (...)
     
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  4.  9
    A logical formalisation of false belief tasks.R. Velázquez-Quesada A. Institute for Logic Anthia Solaki Fernando, Computation Language, Netherlandsb Netherlands Organization for Applied Scientific Research, Media Studies Netherlandsc Information Science & Norway - forthcoming - Journal of Applied Non-Classical Logics:1-51.
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  5. The Philosophy of Computer Languages.Graham White - 2003 - In Luciano Floridi, The Blackwell guide to the philosophy of computing and information. Blackwell. pp. 237–247.
    The prelims comprise: Introduction: Two Semantic Projects History The Uses of Semantics Conclusions.
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  6.  27
    Reflecting on human language through computer languages.Kyo Kageura - 2013 - Semiotica 2013 (195):409-414.
    Journal Name: Semiotica - Journal of the International Association for Semiotic Studies / Revue de l'Association Internationale de Sémiotique Volume: 2013 Issue: 195 Pages: 409-414.
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  7.  54
    Metaphor, Myth, and Computer Language.Robert T. Swank - 1988 - Semiotics:83-89.
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  8.  47
    Computational Investigations of Multiword Chunks in Language Learning.Stewart M. McCauley & Morten H. Christiansen - 2017 - Topics in Cognitive Science 9 (3):637-652.
    Second-language learners rarely arrive at native proficiency in a number of linguistic domains, including morphological and syntactic processing. Previous approaches to understanding the different outcomes of first- versus second-language learning have focused on cognitive and neural factors. In contrast, we explore the possibility that children and adults may rely on different linguistic units throughout the course of language learning, with specific focus on the granularity of those units. Following recent psycholinguistic evidence for the role of multiword chunks (...)
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  9. Languages, machines, and classical computation.Luis M. Augusto - 2019 - London, UK: College Publications.
    3rd ed, 2021. A circumscription of the classical theory of computation building up from the Chomsky hierarchy. With the usual topics in formal language and automata theory.
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  10.  52
    Natural language interfaces and strategic computing.Geoffrey K. Pullum - 1987 - AI and Society 1 (1):47-58.
    Modern weaponry is often too complex for unaided human operation, and is largely or totally controlled by computers. But modern software, particularly artificial intelligence software, exhibits such complexity and inscrutability that there are grave dangers associated with its use in non-benign applications. Recent efforts to make computer systems more accessible to military personnel through natural language processing systems, as proposed in the Strategic Computing Initiative of the Defense Advanced Research Projects Agency, increases rather than decreases the dangers of unpredictable (...)
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  11. Programs, grammars and arguments: A personal view of some connections between computation, language and logic.J. Lambek - 1997 - Bulletin of Symbolic Logic 3 (3):312-328.
    As an undergraduate I was taught to multiply two numbers with the help of log tables, using the formulaHaving graduated to teach calculus to Engineers, I learned that log tables were to be replaced by slide rules. It was then that Imade the fateful decision that there was no need for me to learn how to use this tedious device, as I could always rely on the students to perform the necessary computations. In the course of time, slide rules were (...)
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  12. The computational and the representational language-of-thought hypotheses.David J. Chalmers - 2023 - Behavioral and Brain Sciences 46:e269.
    There are two versions of the language-of-thought hypothesis (LOT): Representational LOT (roughly, structured representation), introduced by Ockham, and computational LOT (roughly, symbolic computation) introduced by Fodor. Like many others, I oppose the latter but not the former. Quilty-Dunn et al. defend representational LOT, but they do not defend the strong computational LOT thesis central to the classical-connectionist debate.
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  13. (1 other version)Language and mentality: Computational, representational, and dispositional conceptions.James H. Fetzer - 1989 - Behaviorism 17 (1):21-39.
    The purpose of this paper is to explore three alternative frameworks for understanding the nature of language and mentality, which accent syntactical, semantical, and pragmatical aspects of the phenomena with which they are concerned, respectively. Although the computational conception currently exerts considerable appeal, its defensibility appears to hinge upon an extremely implausible theory of the relation of form to content. Similarly, while the representational approach has much to recommend it, its range is essentially restricted to those units of (...) that can be understood in terms of undefined units. Thus, the only alternative among these three that can account for the meaning of primitive units of language is one emphasizing the basic role of skills, habits, and tendencies in relating signs and dispositions. (shrink)
     
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  14.  22
    Narcissus in language: A semiotic contrast of natural and computer language through self-reference.Kumiko Tanaka-Ishii - 2008 - Semiotica 2008 (172):299-311.
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  15.  27
    The relevance of philosophical skills in computer language development.John D. Sinks - 1977 - Metaphilosophy 8 (2-3):239-244.
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  16.  1
    Comment on Professor Johnson’s Article on Computer Language.Louise Sundararajan - 1994 - Ultimate Reality and Meaning 17 (4):316-316.
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  17. Computational Complexity of Polyadic Lifts of Generalized Quantifiers in Natural Language.Jakub Szymanik - 2010 - Linguistics and Philosophy 33 (3):215-250.
    We study the computational complexity of polyadic quantifiers in natural language. This type of quantification is widely used in formal semantics to model the meaning of multi-quantifier sentences. First, we show that the standard constructions that turn simple determiners into complex quantifiers, namely Boolean operations, iteration, cumulation, and resumption, are tractable. Then, we provide an insight into branching operation yielding intractable natural language multi-quantifier expressions. Next, we focus on a linguistic case study. We use computational complexity results to (...)
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  18.  90
    A Computational Approach to Quantifiers as an Explanation for Some Language Impairments in Schizophrenia.Marcin Zajenkowski, Rafał Styła & Jakub Szymanik - 2011 - Journal of Communication Disorder 44:2011.
    We compared the processing of natural language quantifiers in a group of patients with schizophrenia and a healthy control group. In both groups, the difficulty of the quantifiers was consistent with computational predictions, and patients with schizophrenia took more time to solve the problems. However, they were significantly less accurate only with proportional quantifiers, like more than half. This can be explained by noting that, according to the complexity perspective, only proportional quantifiers require working memory engagement.
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  19. Logic, Language and Computation.[author unknown] - 2000 - Studia Logica 64 (3):415-421.
  20.  41
    Computational challenges of evolving the language-ready brain.Michael A. Arbib - 2018 - Interaction Studies 19 (1-2):7-21.
    Computational modeling of the macaque brain grounds hypotheses on the brain of LCA-m (the last common ancestor of monkey and human). Elaborations thereof provide a brain model for LCA-c (c for chimpanzee). The Mirror System Hypothesis charts further steps via imitation and pantomime to protosign and protolanguage on the path to a "language-ready brain" inHomo sapiens,with the path to speech being indirect. The material poses new challenges for both experimentation and modeling.
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  21.  22
    Formalizing the Dynamics of Information.Martina Faller, Stefan C. Kaufmann, Marc Pauly & Center for the Study of Language and Information S.) - 2000 - Center for the Study of Language and Information Publications.
    The papers collected in this volume exemplify some of the trends in current approaches to logic, language and computation. Written by authors with varied academic backgrounds, the contributions are intended for an interdisciplinary audience. The first part of this volume addresses issues relevant for multi-agent systems: reasoning with incomplete information, reasoning about knowledge and beliefs, and reasoning about games. Proofs as formal objects form the subject of Part II. Topics covered include: contributions on logical frameworks, linear logic, and (...)
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  22.  10
    A computer model of child language learning.Mallory Selfridge - 1986 - Artificial Intelligence 29 (2):171-216.
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  23.  29
    Natural language at a crossroads: Formal and probabilistic approaches in philosophy and computer science.Paulo Pirozelli & Igor Câmara - 2022 - Manuscrito 45 (2):50-81.
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  24. Applying Computer Software Technology to Develop English as a Foreign Language Vocabulary Acquisition.Rowles Phillip - 2010 - Fenomenologia. Diálogos Possíveis Campinas: Alínea/Goiânia: Editora da Puc Goiás 10:91-100.
     
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  25. Computational Learning Theory and Language Acquisition.Alexander Clark - unknown
    Computational learning theory explores the limits of learnability. Studying language acquisition from this perspective involves identifying classes of languages that are learnable from the available data, within the limits of time and computational resources available to the learner. Different models of learning can yield radically different learnability results, where these depend on the assumptions of the model about the nature of the learning process, and the data, time, and resources that learners have access to. To the extent that such (...)
     
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  26. Language, Logic, and Computation: the 1994 Moraga Proceedings.Dag Westerstahl & Jeremy Seligman (eds.) - 1996 - CSLI.
     
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  27.  36
    Computational models of language processing.Edward P. Stabler - 1986 - Behavioral and Brain Sciences 9 (3):550-551.
  28. Logic, Language and Computation Vol.Lawrence Moss, Gizburg S., Rijke Jonathaden & Maarten (eds.) - 1999 - CSLI Publications.
  29.  4
    Computer models of thought and language.Leonard Uhr - 1975 - Artificial Intelligence 6 (3):289-292.
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  30.  49
    Computer vision, human senses, and language of art.Lev Manovich - 2021 - AI and Society 36 (4):1145-1152.
    What is the most important reason for using Computer Vision methods in humanities research? In this article, I argue that the use of numerical representation and data analysis methods offers a new language for describing cultural artifacts, experiences and dynamics. The human languages such as English or Russian that developed rather recently in human evolution are not good at capturing analog properties of human sensorial and cultural experiences. These limitations become particularly worrying if we want to compare thousands, millions (...)
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  31.  21
    Generalized Quantifiers and Computation, 9th European Summer School in Logic, Language, and Information, ESSLLI'97 Workshop, Aix-en-Provence, France, August 11-22, 1997, Revised Lectures.Jouko Väänänen - 1997 - Springer.
    This book comprises revised full versions of lectures given during the 9th European Summer School in Logic, Languages, and Information, ESSLLI'97, held in Aix-en-Provence, France, in August 1997. The six lectures presented introduce the reader to the state of the art in the area of generalized quantifiers and computation. Besides an introductory survey by the volume editor various aspects of generalized quantifiers are studied in depth.
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  32.  93
    Bridging computational, formal and psycholinguistic approaches to language.Shimon Edelman - unknown
    We compare our model of unsupervised learning of linguistic structures, ADIOS [1, 2, 3], to some recent work in computational linguistics and in grammar theory. Our approach resembles the Construction Grammar in its general philosophy (e.g., in its reliance on structural generalizations rather than on syntax projected by the lexicon, as in the current generative theories), and the Tree Adjoining Grammar in its computational characteristics (e.g., in its apparent affinity with Mildly Context Sensitive Languages). The representations learned by our algorithm (...)
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  33.  49
    A computational model of the cultural co-evolution of language and mindreading.Marieke Woensdregt, Chris Cummins & Kenny Smith - 2020 - Synthese 199 (1-2):1347-1385.
    Several evolutionary accounts of human social cognition posit that language has co-evolved with the sophisticated mindreading abilities of modern humans. It has also been argued that these mindreading abilities are the product of cultural, rather than biological, evolution. Taken together, these claims suggest that the evolution of language has played an important role in the cultural evolution of human social cognition. Here we present a new computational model which formalises the assumptions that underlie this hypothesis, in order to (...)
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  34.  84
    Logic, Language and Computation.Jerry Seligman & Dag Westerstahl (eds.) - 1996 - Center for the Study of Language and Inf.
    This volume presents work that evolved out of the Third Conference on Situation Theory and Its Applications, held at Oiso, Japan, in November of 1991. The chapters presented in this volume continue the mathematical development of situation theory, including the introduction of a graphical notation; and the applications of situation theory discussed are wide-ranging, including topics in natural language semantics and philosophical logic, and exploring the use of information theory in the social sciences. The research presented in this volume (...)
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  35. Logic, Language, Information, and Computation. WoLLIC 2019. Lecture Notes in Computer Science, Vol. 11541.Rosalie Iemhoff, Michael Moortgat & Ruy de Queiroz (eds.) - 2019 - Springer.
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  36.  7
    Logic, Language, Information, and Computation: 22nd International Workshop, WoLLIC 2015, Bloomington, IN, USA, July 20-23, 2015, Proceedings (Lecture Notes in Computer Science Book 9160).Valeria de Paiva, Ruy de Queiroz, Lawrence S. Moss, Daniel Leivant & Anjolina G. De Oliveira - 2015 - Springer.
    Edited in collaboration with FoLLI, the Association of Logic, Language and Information this book constitutes the refereed proceedings of the 22nd Workshop on Logic, Language, Information and Computation, WoLLIC 2015, held in the campus of Indiana University, Bloomington, IN, USA in July 2015. The 14 contributed papers, presented together with 8 invited lectures and 4 tutorials, were carefully reviewed and selected from 44 submissions. The focus of the workshop was on interdisciplinary research involving formal logic, computing and (...)
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  37.  27
    Computational semantics: an introduction to artificial intelligence and natural language comprehension.Eugene Charniak & Yorick Wilks (eds.) - 1976 - New York: distributors for the U.S.A. and Canada, Elsevier/North Holland.
    Linguistics. Artificial intelligence. Related fields. Computation.
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  38.  12
    Machinations: Computational Studies of Logic, Language, and Cognition.Richard Spencer-Smith, Steve Torrance & Stephen B. Torrance - 1992 - Intellect Books.
    This volume brings together a collection of papers covering a wide range of topics in computer and cognitive science. Topics included are: the foundational relevance of logic to computer science, with particular reference to tense logic, constructive logic, and Horn clause logic; logic as the theoretical underpinnings of the engineering discipline of expert systems; a discussion of the evolution of computational linguistics into functionally distinct task levels; and current issues in the implementation of speech act theory.
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  39.  28
    (1 other version)Canalization of Language Structure From Environmental Constraints: A Computational Model of Word Learning From Multiple Cues.Padraic Monaghan - 2016 - Topics in Cognitive Science 8 (4).
    There is substantial variation in language experience, yet there is surprising similarity in the language structure acquired. Constraints on language structure may be external modulators that result in this canalization of language structure, or else they may derive from the broader, communicative environment in which language is acquired. In this paper, the latter perspective is tested for its adequacy in explaining robustness of language learning to environmental variation. A computational model of word learning from (...)
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  40.  67
    Bridging language with the rest of cognition: computational, algorithmic and neurobiological issues and methods.Shimon Edelman - unknown
    The computational program for theoretical neuroscience initiated by Marr and Poggio (1977) calls for a study of biological information processing on several distinct levels of abstraction. At each of these levels — computational (defining the problems and considering possible solutions), algorithmic (specifying the sequence of operations leading to a solution) and implementational — significant progress has been made in the understanding of cognition. In the past three decades, computational principles have been discovered that are common to a wide range of (...)
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  41.  46
    Pristine Perspectives on Logic, Language and Computation : ESSLLI 2012 and ESSLLI 2013 Student Sessions, Selected Papers. [REVIEW]Margot Colinet, Sophia Katrenko & Rasmus Kraemmer Rendsvig - unknown
    The European Summer School in Logic, Language and Information is organized every year by the Association for Logic, Language and Information in different sites around Europe. The main focus of ESSLLI is on the interface between linguistics, logic and computation. ESSLLI offers foundational, introductory and advanced courses, as well as workshops, covering a wide variety of topics within the three areas of interest: Language and Computation, Language and Logic, and Logic and Computation. The (...)
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  42.  29
    Can Students’ Computer Programming Learning Motivation and Effectiveness Be Enhanced by Learning Python Language? A Multi-Group Analysis.Hsiao-Chi Ling, Kuo-Lun Hsiao & Wen-Chiao Hsu - 2021 - Frontiers in Psychology 11.
    Python language has become the most popular computer language. Python is widely adopted in computer courses. However, Python language’s effects on the college and university students’ learning performance, motivations, computer programming self-efficacy, and maladaptive cognition have still not been widely examined. The main objective of this study is to explore the effects of learning Python on students’ programming learning. The junior students of two classes in a college are the research participants. One class was taught Java (...) and the other class was taught Python language. The learning performance, motivations, and maladaptive cognition in the two classes were compared to evaluate the differences. The results showed that the motivations, computer programming self-efficacy, and maladaptive cognition on the learning performance were significant in the Python class. The results and findings of this study can be used in Python course arrangement and development. (shrink)
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  43.  6
    Figurative Language and Sensory Perception: Corpus-Based Computer-Assisted Study of the Nature and Motivation of Synesthetic Metaphors in Olive Oil Tasting Notes.Lucía Sanz-Valdivieso & Belén López Arroyo - 2024 - Metaphor and Symbol 39 (4):260-280.
    Meaning in sensory language is often built through figurative mechanisms, such as synesthetic metaphors, where a sensorial domain is used to talk about perceptions from a different sense, as in sweet[taste] texture[touch]. The motivation of synesthetic transfers of meaning has been studied in general and literary language, resulting in attempts to reveal universal patterns regarding the directionality of meaning transfer and sensorial conceptual preference. However, those universals have not been proven in any sensory Language for Specific Purposes (...)
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  44.  43
    Characterizing language identification in terms of computable numberings.Sanjay Jain & Arun Sharma - 1997 - Annals of Pure and Applied Logic 84 (1):51-72.
    Identification of programs for computable functions from their graphs and identification of grammars for recursively enumerable languages from positive data are two extensively studied problems in the recursion theoretic framework of inductive inference.In the context of function identification, Freivalds et al. have shown that only those collections of functions, , are identifiable in the limit for which there exists a 1-1 computable numbering ψ and a discrimination function d such that1. for each , the number of indices i such that (...)
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  45.  53
    Computer‐aided disease prediction system: development of application software with SAS component language.Chi-Ming Chang, Hsu-Sung Kuo, Shu-Hui Chang, Hong-Jen Chang, Der-Ming Liou, Tabar Laszlo & Tony Hsiu-Hsi Chen - 2005 - Journal of Evaluation in Clinical Practice 11 (2):139-159.
  46. Computability, Complexity and Languages.Martin Davies, Ron Segal & Elaine Weyuker - 1994 - Academic Press.
     
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  47.  21
    Computational theories should be made with natural language instead of meaningless code.Peter DeScioli - 2023 - Behavioral and Brain Sciences 46:e332.
    The target article claims that we should speak in code to understand property, because natural language is too ambiguous. Yet the best computer programmers tell us the opposite: Arbitrary code is too ambiguous, so we should use natural language for variables, functions, and classes. I discuss how meaningless code makes Boyer's theory too enigmatic to properly debate.
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  48.  97
    Intention, interpretation and the computational structure of language.Matthew Stone - 2004 - Cognitive Science 28 (5):781-809.
    I show how a conversational process that takes simple, intuitively meaningful steps may be understood as a sophisticated computation that derives the richly detailed, complex representations implicit in our knowledge of language. To develop the account, I argue that natural language is structured in a way that lets us formalize grammatical knowledge precisely in terms of rich primitives of interpretation. Primitives of interpretation can be correctly viewed intentionally, as explanations of our choices of linguistic actions; the model (...)
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  49. Explanation in Computational Psychology: Language, Perception and Level 1.5.Christopher Peacocke - 1986 - Mind and Language 1 (2):101-123.
  50.  10
    Language barrier” in theories of mind and limitations of the computational approach.П. Н Барышников - 2024 - Philosophy Journal 17 (2):122-136.
    This paper examines from a special perspective the problem of methodological limita­tions of the computational approach in the philosophy of mind and empirical sciences. The main goal is to consistently substantiate the dependence of philosophical “metaphori­cal dictionaries” on advances in the field of computer science, historical contexts of epis­temology, formal and methodological limitations of algorithmic and computational proce­dures. The key idea is that despite the success of computational models in empirical re­search, their conceptual level does not allow us to correctly (...)
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