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William J. Rapaport [34]William Rapaport [1]
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William J. Rapaport
State University of New York, Buffalo
  1.  28
    Syntax, Semantics, and Computer Programs.William J. Rapaport - forthcoming - Philosophy and Technology:1-13.
    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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  2. Philosophy of Computer Science: An Introductory Course.William J. Rapaport - 2005 - Teaching Philosophy 28 (4):319-341.
    There are many branches of philosophy called “the philosophy of X,” where X = disciplines ranging from history to physics. The philosophy of artificial intelligence has a long history, and there are many courses and texts with that title. Surprisingly, the philosophy of computer science is not nearly as well-developed. This article proposes topics that might constitute the philosophy of computer science and describes a course covering those topics, along with suggested readings and assignments.
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  3. 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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  4. 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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  5. 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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  6. Non-Existent Objects and Epistemological Ontology.William J. Rapaport - 1985 - Grazer Philosophische Studien 25:61-95.
    This essay examines the role of non-existent objects in "epistemological ontology" — the study of the entities that make thinking possible. An earlier revision of Meinong's Theory of Objects is reviewed, Meinong's notions of Quasisein and Außersein are discussed, and a theory of Meinongian objects as "combinatorially possible" entities is presented.
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  7. Syntactic Semantics: Foundations of Computational Natural Language Understanding.William J. Rapaport - 1988 - In James H. Fetzer (ed.), Aspects of AI. Kluwer Academic Publishers.
    This essay considers what it means to understand natural language and whether a computer running an artificial-intelligence program designed to understand natural language does in fact do so. It is argued that a certain kind of semantics is needed to understand natural language, that this kind of semantics is mere symbol manipulation (i.e., syntax), and that, hence, it is available to AI systems. Recent arguments by Searle and Dretske to the effect that computers cannot understand natural language are discussed, and (...)
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  8. 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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  9. 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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  10. 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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  11. A Computational Theory of Perspective and Reference in Narrative.Janyce M. Wiebe & William J. Rapaport - 1988 - In Proceedings of the 26th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics. pp. 131-138.
    Narrative passages told from a character's perspective convey the character's thoughts and perceptions. We present a discourse process that recognizes characters'.
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  12. Yes, She Was! Reply to Ford’s “Helen KellerWas 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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  13. Models and Minds.Stuart C. Shapiro & William J. Rapaport - 1991 - In Robert E. Cummins & John L. Pollock (eds.), Philosophy and AI. Cambridge: MIT Press. pp. 215--259.
    Cognitive agents, whether human or computer, that engage in natural-language discourse and that have beliefs about the beliefs of other cognitive agents must be able to represent objects the way they believe them to be and the way they believe others believe them to be. They must be able to represent other cognitive agents both as objects of beliefs and as agents of beliefs. They must be able to represent their own beliefs, and they must be able to represent beliefs (...)
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  14. Understanding Understanding: Syntactic Semantics and Computational Cognition.William J. Rapaport - 1995 - Philosophical Perspectives 9:49-88.
    John Searle once said: "The Chinese room shows what we knew all along: syntax by itself is not sufficient for semantics. (Does anyone actually deny this point, I mean straight out? Is anyone actually willing to say, straight out, that they think that syntax, in the sense of formal symbols, is really the same as semantic content, in the sense of meanings, thought contents, understanding, etc.?)." I say: "Yes". Stuart C. Shapiro has said: "Does that make any sense? Yes: Everything (...)
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  15. On Epistemic Logic and Logical Omniscience.William J. Rapaport & Moshe Y. Vardi - 1988 - Journal of Symbolic Logic 53 (2):668.
    Review of Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning About Knowledge: Proceedings of the 1986 Conference (Los Altos, CA: Morgan Kaufmann, 1986),.
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  16. To Think or Not to Think.William J. Rapaport - 1988 - Noûs 22 (4):585-609.
    A critical study of John Searle's Minds, Brains and Science (Cambridge, MA: Harvard University Press, 1984).
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  17. The SNePS Family.Stuart C. Shapiro & William J. Rapaport - 1992 - Computers and Mathematics with Applications 23:243-275.
    SNePS, the Semantic Network Processing System 45, 54], has been designed to be a system for representing the beliefs of a natural-language-using intelligent system (a \cognitive agent"). It has always been the intention that a SNePS-based \knowledge base" would ultimatelybe built, not by a programmeror knowledge engineer entering representations of knowledge in some formallanguage or data entry system, but by a human informing it using a natural language (NL) (generally supposed to be English), or by the system reading books or (...)
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  18. A Triage Theory of Grading: The Good, the Bad, and the Middling.William J. Rapaport - 2011 - Teaching Philosophy 34 (4):347–372.
    This essay presents and defends a triage theory of grading: An item to be graded should get full credit if and only if it is clearly or substantially correct, minimal credit if and only if it is clearly or substantially incorrect, and partial credit if and only if it is neither of the above; no other (intermediate) grades should be given. Details on how to implement this are provided, and further issues in the philosophy of grading (reasons for and against (...)
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  19. 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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  20. 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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  21. Logical Foundations for Belief Representation.William Rapaport - 1986 - Cognitive Science 10 (4):371-422.
    This essay presents a philosophical and computational theory of the representation of de re, de dicto, nested, and quasi-indexical belief reports expressed in natural language. The propositional Semantic Network Processing System (SNePS) is used for representing and reasoning about these reports. In particular, quasi-indicators (indexical expressions occurring in intentional contexts and representing uses of indicators by another speaker) pose problems for natural-language representation and reasoning systems, because--unlike pure indicators--they cannot be replaced by coreferential NPs without changing the meaning of the (...)
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  22. The Inner Mind and the Outer World: Guest Editor's Introduction to a Special Issue on Cognitive Science and Artificial Intelligence.William J. Rapaport - 1991 - Noûs 25 (4):405-410.
    It is well known that people from other disciplines have made significant contributions to philosophy and have influenced philosophers. It is also true (though perhaps not often realized, since philosophers are not on the receiving end, so to speak) that philosophers have made significant contributions to other disciplines and have influenced researchers in these other disciplines, sometimes more so than they have influenced philosophy itself. But what is perhaps not as well known as it ought to be is that researchers (...)
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  23. Ethical Issues in the Use of Computers.William J. Rapaport - 1986 - Teaching Philosophy 9 (3):275-278.
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  24.  28
    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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  25. Philosophy of Artificial Intelligence: A Course Outline.William J. Rapaport - 1986 - Teaching Philosophy 9 (2):103-120.
    In the Fall of 1983, I offered a junior/senior-level course in Philosophy of Artificial Intelligence, in the Department of Philosophy at SUNY Fredonia, after returning there from a year’s leave to study and do research in computer science and artificial intelligence (AI) at SUNY Buffalo. Of the 30 students enrolled, most were computerscience majors, about a third had no computer background, and only a handful had studied any philosophy. (I might note that enrollments have subsequently increased in the Philosophy Department’s (...)
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  26. Because Mere Calculating Isn't Thinking: Comments on Hauser's Why Isn't My Pocket Calculator a Thinking Thing?.William J. Rapaport - 1993 - Minds and Machines 3 (1):11-20.
    This report consists of three papers: “Why Isn’t My Pocket Calculator a Thinking Thing?”, by Larry Hauser; “Because Mere Calculating Isn’t Thinking” (comments on Hauser’s paper), by William J. Rapaport; and “The Sense of ‘Thinking’,” Hauser’s reply. They were originally presented at the Colloquium on Philosophy of Mind at the American Philosophical Association Central Division meeting in Chicago, 27 April 1991. Hauser argues that his pocket calculator (Cal) has certain arithmetical abilities: it seems Cal calculates. That calculating is thinking seems (...)
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  27. Meinong, Alexius; I: Meinongian Semantics.William J. Rapaport - 1991 - In Hans Burkhardt & Barry Smith (eds.), Handbook of Metaphysics and Ontology. Philosophia Verlag. pp. 516-519.
    A brief introduction to Meinong, his theory of objects, and modern interpretations of it. Sections include: The Theory of Objects, Castañeda's Theory of Guises, Parsons,'s Theory of Nonexistent Objects, Rapaport's Theory of Meinongian Objects, Routley's Theory of Items.
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  28. Review: Karel Lambert, Meinong and the Principle of Independence. Its Place in Meinong's Theory of Objects and Its Significance in Contemporary Philosophical Logic. [REVIEW]William J. Rapaport - 1986 - Journal of Symbolic Logic 51 (1):248-252.
    Review of Karel Lambert, Meinong and the Principle of Independence: Its Place in Meinong's Theory of Objects and Its Significance in Contemporary Philosophical Logic.
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  29. CASTANEDA, Hector-Neri (1924–1991).William J. Rapaport - 2005 - In John R. Shook (ed.), The Dictionary of Modern American Philosophers, 1860-1960. Thoemmes Press.
    H´ector-Neri Casta˜neda-Calder´on (December 13, 1924–September 7, 1991) was born in San Vicente Zacapa, Guatemala. He attended the Normal School for Boys in Guatemala City, later called the Military Normal School for Boys, from which he was expelled for refusing to fight a bully; the dramatic story, worthy of being filmed, is told in the “De Re” section of his autobiography, “Self-Profile” (1986). He then attended a normal school in Costa Rica, followed by studies in philosophy at the University of San (...)
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  30. On Cogito Propositions.William J. Rapaport - 1976 - Philosophical Studies 29 (1):63-68.
    I argue that George Nakhnikian's analysis of the logic of cogito propositions (roughly, Descartes's 'cogito' and 'sum') is incomplete. The incompleteness is rectified by showing that disjunctions of cogito propositions with contingent, non-cogito propositions satisfy conditions of incorrigibility, self-certifyingness, and pragmatic consistency; hence, they belong to the class of propositions with whose help a complete characterization of cogito propositions is made possible.
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  31.  61
    Meinong, Defective Objects, and Logical Paradox.William J. Rapaport - 1982 - Grazer Philosophische Studien 18 (1):17-39.
    Alexius Meinong developed a notion of defective objects in order to account for various logical and psychological paradoxes. The notion is of historical interest, since it presages recent work on the logical paradoxes by Herzberger and Kripke. But it fails to do the job it was designed for. However, a technique implicit in Meinong's investigation is more successful and can be adapted to resolve a similar paradox discovered by Romane Clark in a revised version of Meinong's Theory of Objects due (...)
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  32. God, the Demon, and the Cogito.William J. Rapaport - manuscript
    The purpose of this essay is to exhibit in detail the setting for the version of the Cogito Argument that appears in Descartes’s Meditations. I believe that a close reading of the text can shed new light on the nature and role of the “evil demon”, on the nature of God as he appears in the first few Meditations, and on the place of the Cogito Argument in Descartes’s overall scheme.
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  33. Philosophy for Children and Other People.William J. Rapaport - 1987 - American Philosophical Association Newsletter on Teaching Philosophy (Summer):19-22.
    It is a matter of fact—and has been so for a considerable amount of time—that philosophy is taught at the pre—college level. However, to teach philosophy at that (or at any) level is one thing; to teach it well is quite another. Fortunately, it can be taught well, as a host of successful experiences and programs have shown. But in what ways can it be taught? Are there differences in the ways in which it can or should be taught at (...)
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  34.  48
    Proceedings of the 26th Annual Meeting of the Association for Computational Linguistics (SUNY Buffalo).Janyce M. Wiebe & William J. Rapaport (eds.) - 1988 - Assoc for computational linguistics.
    Narrative passages told from a character's perspective convey the character's thoughts and perceptions. We present a discourse process that recognizes characters' thoughts and perceptions in third-person narrative. An effect of perspective on reference In narrative is addressed: references in passages told from the perspective of a character reflect the character's beliefs. An algorithm that uses the results of our discourse process to understand references with respect to an appropriate set of beliefs is presented.
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