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  1. Meaning Relations, Syntax, and Understanding.Prakash Mondal - 2022 - Axiomathes 32 (3):459-475.
    This paper revisits the conception of intelligence and understanding as embodied in the Turing Test. It argues that a simple system of meaning relations drawn from words/lexical items in a natural language and framed in terms of syntax-free relations in linguistic texts can help ground linguistic inferences in a manner that can be taken to be 'understanding' in a mechanized system. Understanding in this case is a matter of running through the relevant inferences meaning relations allow for, and some of (...)
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  • (1 other version)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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  • (1 other version)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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  • 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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  • 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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  • 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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  • Semiotic Systems, Computers, and the Mind: How Cognition Could Be Computing.William J. Rapaport - 2012 - International Journal of Signs and Semiotic Systems 2 (1):32-71.
    In this reply to James H. Fetzer’s “Minds and Machines: Limits to Simulations of Thought and Action”, I argue that computationalism should not be the view that (human) cognition is computation, but that it should be the view that cognition (simpliciter) is computable. It follows that computationalism can be true even if (human) cognition is not the result of computations in the brain. I also argue that, if semiotic systems are systems that interpret signs, then both humans and computers are (...)
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  • How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room.William J. Rapaport - 2006 - Minds and Machines 16 (4):381-436.
    A computer can come to understand natural language the same way Helen Keller did: by using “syntactic semantics”—a theory of how syntax can suffice for semantics, i.e., how semantics for natural language can be provided by means of computational symbol manipulation. This essay considers real-life approximations of Chinese Rooms, focusing on Helen Keller’s experiences growing up deaf and blind, locked in a sort of Chinese Room yet learning how to communicate with the outside world. Using the SNePS computational knowledge-representation system, (...)
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  • Yes, She Was!: Reply to Ford’s “Helen Keller Was Never in a Chinese Room”.William J. Rapaport - 2011 - Minds and Machines 21 (1):3-17.
    Ford’s Helen Keller Was Never in a Chinese Room claims that my argument in How Helen Keller Used Syntactic Semantics to Escape from a Chinese Room fails because Searle and I use the terms ‘syntax’ and ‘semantics’ differently, hence are at cross purposes. Ford has misunderstood me; this reply clarifies my theory.
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  • The Turing test.Graham Oppy & D. Dowe - 2003 - Stanford Encyclopedia of Philosophy.
    This paper provides a survey of philosophical discussion of the "the Turing Test". In particular, it provides a very careful and thorough discussion of the famous 1950 paper that was published in Mind.
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  • From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness (Part 3).Jeffrey White & Jun Tani - 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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  • In Defense of Contextual Vocabulary Acquisition: How to Do Things with Words in Context.William J. Rapaport - 2005 - In Anind Dey, Boicho Kokinov, David Leake & Roy Turner (eds.), Proceedings of the 5th International and Interdisciplinary Conference on Modeling and Using Context. Springer-Verlag Lecture Notes in Artificial Intelligence 3554. pp. 396--409.
    Contextual vocabulary acquisition (CVA) is the deliberate acquisition of a meaning for a word in a text by reasoning from context, where “context” includes: (1) the reader’s “internalization” of the surrounding text, i.e., the reader’s “mental model” of the word’s “textual context” (hereafter, “co-text” [3]) integrated with (2) the reader’s prior knowledge (PK), but it excludes (3) external sources such as dictionaries or people. CVA is what you do when you come across an unfamiliar word in your reading, realize that (...)
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  • What did you mean by that? Misunderstanding, negotiation, and syntactic semantics.William J. Rapaport - 2003 - Minds and Machines 13 (3):397-427.
    Syntactic semantics is a holistic, conceptual-role-semantic theory of how computers can think. But Fodor and Lepore have mounted a sustained attack on holistic semantic theories. However, their major problem with holism (that, if holism is true, then no two people can understand each other) can be fixed by means of negotiating meanings. Syntactic semantics and Fodor and Lepore’s objections to holism are outlined; the nature of communication, miscommunication, and negotiation is discussed; Bruner’s ideas about the negotiation of meaning are explored; (...)
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  • Intelligence as a Social Concept: a Socio-Technological Interpretation of the Turing Test.Shlomo Danziger - 2022 - Philosophy and Technology 35 (3):1-26.
    Alan Turing’s 1950 imitation game has been widely understood as a means for testing if an entity is intelligent. Following a series of papers by Diane Proudfoot, I offer a socio-technological interpretation of Turing’s paper and present an alternative way of understanding both the imitation game and Turing’s concept of intelligence. Turing, I claim, saw intelligence as a social concept, meaning that possession of intelligence is a property determined by society’s attitude toward the entity. He realized that as long as (...)
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  • Do Computers "Have Syntax, But No Semantics"?Jaroslav Peregrin - 2021 - Minds and Machines 31 (2):305-321.
    The heyday of discussions initiated by Searle's claim that computers have syntax, but no semantics has now past, yet philosophers and scientists still tend to frame their views on artificial intelligence in terms of syntax and semantics. In this paper I do not intend to take part in these discussions; my aim is more fundamental, viz. to ask what claims about syntax and semantics in this context can mean in the first place. And I argue that their sense is so (...)
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  • Různé pohledy na otázku: Mohou stroje myslet?Ondřej Vadinský - 2011 - E-Logos 18 (1):1-24.
    Tato práce se zabývá otázkou, zda mohou stroje myslet. Sleduje tedy proměny její tematizace u~vybraných filosofů a myslitelů, jimiž jsou: Descartův dualizmus, Turingův test, Searlův čínský pokoj, umělé neuronové sítě manželů Churchlandových a Rapaportova abstrakce a implementace a syntaktická sémantika. Poté, co ukáže, jak se tyto tematizace liší a v~čem se naopak shodují, ptá se práce po povaze vztahu mezi myšlením a jeho projevy, který je ústřední pro oprávněnost Turingova testu. Dále práce akcentuje nutnost kombinace vhodné rozlišovací schopnosti s~reprezentativní mírou (...)
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  • (1 other version)The philosophy of computer science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
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  • Book Reviews. [REVIEW][author unknown] - 2006 - Australasian Journal of Philosophy 84 (1):129-145.
    Preston, John, and Mark Bishop, eds., Views into the Chinese Room: New Essays on Searle and Artificial Intelligence, Oxford: Clarendon Press, 2002, pp. xvi + 410, US$99.00, US$39.95...
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