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  1. Computers Are Syntax All the Way Down: Reply to Bozşahin.William J. Rapaport - 2019 - Minds and Machines 29 (2):227-237.
    A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.
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  • What is a Computer? A Survey.William J. Rapaport - 2018 - Minds and Machines 28 (3):385-426.
    A critical survey of some attempts to define ‘computer’, beginning with some informal ones, then critically evaluating those of three philosophers, and concluding with an examination of whether the brain and the universe are computers.
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  • From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness (Part 3).Jeffrey White - 2017 - APA Newsletter on Philosophy and Computers 17 (1):11-22.
    This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by forecasting (...)
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  • Synchronous Online Philosophy Courses: An Experiment in Progress.Fritz McDonald - 2018 - APA Newsletter on Philosophy and Computers 18 (1):37-40.
    There are two main ways to teach a course online: synchronously or asynchronously. In an asynchronous course, students can log on at their convenience and do the course work. In a synchronous course, there is a requirement that all students be online at specific times, to allow for a shared course environment. In this article, the author discusses the strengths and weaknesses of synchronous online learning for the teaching of undergraduate philosophy courses. The author discusses specific strategies and technologies he (...)
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  • On Evolution of Thinking About Semiosis: Semiotics Meets Cognitive Science.Piotr Konderak - 2017 - Avant: Trends in Interdisciplinary Studies 7 (2):82-103.
    The aim of the paper is to sketch an idea—seen from the point of view of a cognitive scientist—of cognitive semiotics as a discipline. Consequently, the article presents aspects of the relationship between the two disciplines: semiotics and cognitive science. The main assumption of the argumentation is that at least some semiotic processes are also cognitive processes. At the methodological level, this claim allows for application of cognitive models as explanations of selected semiotic processes. In particular, the processes of embedded (...)
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  • Does Computation Reveal Machine Cognition?Prakash Mondal - 2014 - Biosemiotics 7 (1):97-110.
    This paper seeks to understand machine cognition. The nature of machine cognition has been shrouded in incomprehensibility. We have often encountered familiar arguments in cognitive science that human cognition is still faintly understood. This paper will argue that machine cognition is far less understood than even human cognition despite the fact that a lot about computer architecture and computational operations is known. Even if there have been putative claims about the transparency of the notion of machine computations, these claims do (...)
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  • Computers Are Syntax All the Way Down: Reply to Bozşahin.William J. Rapaport - 2019 - Minds and Machines 29 (2):227-237.
    A response to a recent critique by Cem Bozşahin of the theory of syntactic semantics as it applies to Helen Keller, and some applications of the theory to the philosophy of computer science.
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  • Syntax, Semantics, and Computer Programs.William J. Rapaport - 2020 - Philosophy and Technology 33 (2):309-321.
    Turner argues that computer programs must have purposes, that implementation is not a kind of semantics, and that computers might need to understand what they do. I respectfully disagree: Computer programs need not have purposes, implementation is a kind of semantic interpretation, and neither human computers nor computing machines need to understand what they do.
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  • Why Think That the Brain is Not a Computer?Marcin Miłkowski - 2016 - APA Newsletter on Philosophy and Computers 16 (2):22-28.
    In this paper, I review the objections against the claim that brains are computers, or, to be precise, information-processing mechanisms. By showing that practically all the popular objections are either based on uncharitable interpretation of the claim, or simply wrong, I argue that the claim is likely to be true, relevant to contemporary cognitive (neuro)science, and non-trivial.
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  • The Philosophy of Computer Science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
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  • Meinongian Semantics and Artificial Intelligence.William J. Rapaport - 2013 - Humana Mente 6 (25):25-52.
    This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.
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  • What an Algorithm Is.Robin Hill - 2016 - Philosophy and Technology 29 (1):35-59.
    The algorithm, a building block of computer science, is defined from an intuitive and pragmatic point of view, through a methodological lens of philosophy rather than that of formal computation. The treatment extracts properties of abstraction, control, structure, finiteness, effective mechanism, and imperativity, and intentional aspects of goal and preconditions. The focus on the algorithm as a robust conceptual object obviates issues of correctness and minimality. Neither the articulation of an algorithm nor the dynamic process constitute the algorithm itself. Analysis (...)
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