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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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  • Abstract argumentation systems.Gerard A. W. Vreeswijk - 1997 - Artificial Intelligence 90 (1-2):225-279.
  • European Summer Meeting of the Association for Symbolic Logic.E. -J. Thiele - 1992 - Journal of Symbolic Logic 57 (1):282-351.
  • The glair cognitive architecture.Stuart C. Shapiro & Jonathan P. Bona - 2010 - International Journal of Machine Consciousness 2 (2):307-332.
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  • Resolving ambiguity in nonmonotonic inheritance hierarchies.Lynn Andrea Stein - 1992 - Artificial Intelligence 55 (2-3):259-310.
  • Mark H. Bickhard and Loren terveen, foundational issues in artificial intelligence and cognitive science: Impasse and solution, advances in psychology, vol. 109. [REVIEW]Valerie L. Shalin - 2000 - Minds and Machines 10 (3):435-439.
  • Quasi‐Indexicals and Knowledge Reports.William J. Rapaport, Stuart C. Shapiro & Janyce M. Wiebe - 1997 - Cognitive Science 21 (1):63-107.
    We present a computational analysis of de re, de dicto, and de se belief and knowledge reports. Our analysis solves a problem first observed by Hector-Neri Castañeda, namely, that the simple rule -/- `(A knows that P) implies P' -/- apparently does not hold if P contains a quasi-indexical. We present a single rule, in the context of a knowledge-representation and reasoning system, that holds for all P, including those containing quasi-indexicals. In so doing, we explore the difference between reasoning (...)
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  • Predication, fiction, and artificial intelligence.William J. Rapaport - 1991 - Topoi 10 (1):79-111.
    This paper describes the SNePS knowledge-representation and reasoning system. SNePS is an intensional, propositional, semantic-network processing system used for research in AI. We look at how predication is represented in such a system when it is used for cognitive modeling and natural-language understanding and generation. In particular, we discuss issues in the representation of fictional entities and the representation of propositions from fiction, using SNePS. We briefly survey four philosophical ontological theories of fiction and sketch an epistemological theory of fiction (...)
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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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  • Holism, conceptual-role semantics, and syntactic semantics.William J. Rapaport - 2002 - Minds and Machines 12 (1):3-59.
    This essay continues my investigation of `syntactic semantics': the theory that, pace Searle's Chinese-Room Argument, syntax does suffice for semantics (in particular, for the semantics needed for a computational cognitive theory of natural-language understanding). Here, I argue that syntactic semantics (which is internal and first-person) is what has been called a conceptual-role semantics: The meaning of any expression is the role that it plays in the complete system of expressions. Such a `narrow', conceptual-role semantics is the appropriate sort of semantics (...)
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  • Contextual Vocabulary Acquisition: from Algorithm to Curriculum.Michael W. Kibby & William J. Rapaport - 2014 - In Adriano Palma (ed.), Castañeda and His Guises: Essays on the Work of Hector-Neri Castañeda. De Gruyter. pp. 107-150.
    Deliberate contextual vocabulary acquisition (CVA) is a reader’s ability to figure out a (not the) meaning for an unknown word from its “context”, without external sources of help such as dictionaries or people. The appropriate context for such CVA is the “belief-revised integration” of the reader’s prior knowledge with the reader’s “internalization” of the text. We discuss unwarranted assumptions behind some classic objections to CVA, and present and defend a computational theory of CVA that we have adapted to a new (...)
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  • Truth and meaning.Donald Perlis - 1989 - Artificial Intelligence 39 (2):245-250.
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  • In defense of the Turing test.Eric Neufeld & Sonje Finnestad - 2020 - AI and Society 35 (4):819-827.
    In 2014, widespread reports in the popular media that a chatbot named Eugene Goostman had passed the Turing test became further grist for those who argue that the diversionary tactics of chatbots like Goostman and others, such as those who participate in the Loebner competition, are enabled by the open-ended dialog of the Turing test. Some claim a new kind of test of machine intelligence is needed, and one community has advanced the Winograd schema competition to address this gap. We (...)
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  • A general framework for reason maintenance.Drew McDermott - 1991 - Artificial Intelligence 50 (3):289-329.
  • A model for belief revision.João P. Martins & Stuart C. Shapiro - 1988 - Artificial Intelligence 35 (1):25-79.
  • Reaching agreements through argumentation: a logical model and implementation.Sarit Kraus, Katia Sycara & Amir Evenchik - 1998 - Artificial Intelligence 104 (1-2):1-69.
  • Logical reasoning in natural language: It is all about knowledge. [REVIEW]Lucja Iwańska - 1993 - Minds and Machines 3 (4):475-510.
    A formal, computational, semantically clean representation of natural language is presented. This representation captures the fact that logical inferences in natural language crucially depend on the semantic relation of entailment between sentential constituents such as determiner, noun, adjective, adverb, preposition, and verb phrases.The representation parallels natural language in that it accounts for human intuition about entailment of sentences, it preserves its structure, it reflects the semantics of different syntactic categories, it simulates conjunction, disjunction, and negation in natural language by computable (...)
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  • A Reason Maintenance Perspective On Relevant Ramsey Conditionals.Haythem Ismail - 2010 - Logic Journal of the IGPL 18 (4):508-529.
    This paper presents a Ramsey account of conditionals within the framework of an implemented reason maintenance system. The reason maintenance system is built on top of a deductive reasoning engine based on relevance logic. Thus, the account of conditionals provided is not susceptible to the fallacies of relevance. In addition, it is shown that independently motivated requirements on practical relevant reason maintenance allow us to gracefully circumvent Gärdenfors's triviality result.
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  • Andy Clark, jesús Ezquerro, and jesús M. Larrazabal (eds.), Philosophy and cognitive science: Catergories, consciousness, and reasoning. [REVIEW]Bipin Indurkhya - 2000 - Minds and Machines 10 (3):430-435.
  • Knowledge-level analysis of belief base operations.Sven Ove Hansson - 1996 - Artificial Intelligence 82 (1-2):215-235.
  • How not to change the theory of theory change: A reply to Tennant.Sven Ove Hansson & Hans Rott - 1995 - British Journal for the Philosophy of Science 46 (3):361-380.
    A number of seminal papers on the logic of belief change by Alchourrön, Gärden-fors, and Makinson have given rise to what is now known as the AGM paradigm. The present discussion note is a response to Neil Tennant's [1994], which aims at a critical appraisal of the AGM approach and the introduction of an alternative approach. We show that important parts of Tennants's critical remarks are based on misunderstandings or on lack of information. In the course of doing this, we (...)
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  • A sense-based, process model of belief.Robert F. Hadley - 1991 - Minds and Machines 1 (3):279-320.
    A process-oriented model of belief is presented which permits the representation of nested propositional attitudes within first-order logic. The model (NIM, for nested intensional model) is axiomatized, sense-based (via intensions), and sanctions inferences involving nested epistemic attitudes, with different agents and different times. Because NIM is grounded upon senses, it provides a framework in which agents may reason about the beliefs of another agent while remaining neutral with respect to the syntactic forms used to express the latter agent's beliefs. Moreover, (...)
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  • Belief revision in non-classical logics.Dov Gabbay, Odinaldo Rodrigues & Alessandra Russo - 2008 - Review of Symbolic Logic 1 (3):267-304.
    In this article, we propose a belief revision approach for families of (non-classical) logics whose semantics are first-order axiomatisable. Given any such (non-classical) logic , the approach enables the definition of belief revision operators for , in terms of a belief revision operation satisfying the postulates for revision theory proposed by Alchourrrdenfors and Makinson (AGM revision, Alchourrukasiewicz's many-valued logic. In addition, we present a general methodology to translate algebraic logics into classical logic. For the examples provided, we analyse in what (...)
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  • AGM 25 Years: Twenty-Five Years of Research in Belief Change.Eduardo Fermé & Sven Ove Hansson - 2011 - Journal of Philosophical Logic 40 (2):295 - 331.
    The 1985 paper by Carlos Alchourrón (1931–1996), Peter Gärdenfors, and David Makinson (AGM), "On the Logic of Theory Change: Partial Meet Contraction and Revision Functions" was the starting-point of a large and rapidly growing literature that employs formal models in the investigation of changes in belief states and databases. In this review, the first twentyfive years of this development are summarized. The topics covered include equivalent characterizations of AGM operations, extended representations of the belief states, change operators not included in (...)
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  • AGM 25 Years: Twenty-Five Years of Research in Belief Change.Eduardo Fermé & Sven Ove Hansson - 2011 - Journal of Philosophical Logic 40 (2):295-331.
    The 1985 paper by Carlos Alchourrón, Peter Gärdenfors, and David Makinson, “On the Logic of Theory Change: Partial Meet Contraction and Revision Functions” was the starting-point of a large and rapidly growing literature that employs formal models in the investigation of changes in belief states and databases. In this review, the first twenty-five years of this development are summarized. The topics covered include equivalent characterizations of AGM operations, extended representations of the belief states, change operators not included in the original (...)
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  • Logic and artificial intelligence: Divorced, still married, separated ...? [REVIEW]Selmer Bringsjord & David A. Ferrucci - 1998 - Minds and Machines 8 (2):273-308.
    Though it''s difficult to agree on the exact date of their union, logic and artificial intelligence (AI) were married by the late 1950s, and, at least during their honeymoon, were happily united. What connubial permutation do logic and AI find themselves in now? Are they still (happily) married? Are they divorced? Or are they only separated, both still keeping alive the promise of a future in which the old magic is rekindled? This paper is an attempt to answer these questions (...)
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  • Belief ascription, metaphor, and intensional identification.Afzal Ballim, Yorick Wilks & John Barnden - 1991 - Cognitive Science 15 (1):133-171.
    This article discusses the extension of ViewGen, an algorithm derived for belief ascription, to the areas of intensional object identification and metaphor. ViewGen represents the beliefs of agents as explicit, partitioned proposition sets known as environments. Environments are convenient, even essential, for addressing important pragmatic issues of reasoning. The article concentrates on showing that the transformation of information in metaphors, intensional object identification, and ordinary, nonmetaphorical belief ascription can all be seen as different manifestations of a single environment-amalgamation process. The (...)
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  • The philosophy of computer science.Raymond Turner - 2013 - Stanford Encyclopedia of Philosophy.
  • Cognitive and Computer Systems for Understanding Narrative Text.William J. Rapaport, Erwin M. Segal, Stuart C. Shapiro, David A. Zubin, Gail A. Bruder, Judith Felson Duchan & David M. Mark - manuscript
    This project continues our interdisciplinary research into computational and cognitive aspects of narrative comprehension. Our ultimate goal is the development of a computational theory of how humans understand narrative texts. The theory will be informed by joint research from the viewpoints of linguistics, cognitive psychology, the study of language acquisition, literary theory, geography, philosophy, and artificial intelligence. The linguists, literary theorists, and geographers in our group are developing theories of narrative language and spatial understanding that are being tested by the (...)
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  • Contextual Vocabulary Acquisition: A Computational Theory and Educational Curriculum.William J. Rapaport & Michael W. Kibby - 2002 - In Nagib Callaos, Ana Breda & Ma Yolanda Fernandez J. (eds.), Proceedings of the 6th World Multiconference on Systemics, Cybernetics and Informatics. International Institute of Informatics and Systemics.
    We discuss a research project that develops and applies algorithms for computational contextual vocabulary acquisition (CVA): learning the meaning of unknown words from context. We try to unify a disparate literature on the topic of CVA from psychology, first- and secondlanguage acquisition, and reading science, in order to help develop these algorithms: We use the knowledge gained from the computational CVA system to build an educational curriculum for enhancing students’ abilities to use CVA strategies in their reading of science texts (...)
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  • What Is the “Context” for Contextual Vocabulary Acquisition?William J. Rapaport - 2003 - Proceedings of the 4th Joint International Conference on Cognitive Science/7th Australasian Society for Cognitive Science Conference 2:547-552.
    “Contextual” vocabulary acquisition is the active, deliberate acquisition of a meaning for a word in a text by reasoning from textual clues and prior knowledge, including language knowledge and hypotheses developed from prior encounters with the word, but without external sources of help such as dictionaries or people. But what is “context”? Is it just the surrounding text? Does it include the reader’s background knowledge? I argue that the appropriate context for contextual vocabulary acquisition is the reader’s “internalization” of the (...)
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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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