William J. Rapaport State University of New York at Buffalo
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  1. William J. Rapaport, God, the Demon, and the Cogito.
    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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  2. William J. Rapaport & Michael W. Kibby, Contextual Vocabulary Acquisition: From Algorithm to Curriculum.
    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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  3. William J. Rapaport, Erwin M. Segal, Stuart C. Shapiro, David A. Zubin, Gail A. Bruder, Judith Felson Duchan & David M. Mark, Cognitive and Computer Systems for Understanding Narrative Text.
    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. William J. Rapaport (forthcoming). Non-Existent Objects and Epistemological Ontology. 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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  5. William J. Rapaport (2012). Semiotic Systems, Computers, and the Mind: How Cognition Could Be Computing. 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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  6. William Rapaport (2011). Yes, She Was! Reply to Ford’s “Helen KellerWas Never in a Chinese Room”. Minds and Machines 21 (1):3-17.
    Ford’s <span class='Hi'>Helen</span> <span class='Hi'>Keller</span> Was Never in a Chinese Room claims that my argument in How <span class='Hi'>Helen</span> <span class='Hi'>Keller</span> 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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  7. William Rapaport (2011). Yes, She Was! 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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  8. William J. Rapaport (2011). A Triage Theory of Grading: The Good, the Bad, and the Middling. 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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  9. William J. Rapaport (2011). How to Study: A Brief Guide. World Wide Web.
    Everyone has a different "learning style". (A good introduction to the topic of learning styles is Claxton & Murrell 1987. For more on different learning styles, see Keirsey Temperament and Character Web Site, William Perry's Scheme of Intellectual and Ethical Development, Holland 1966, Kolb 1984, Sternberg 1999. For an interesting discussion of some limitations of learning styles from the perspective of teaching styles, see Glenn 2009/2010.) For some online tools targeted at different learning styles, see "100 Helpful Web Tools for (...)
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  10. William J. Rapaport (2006). How Helen Keller Used Syntactic Semantics to Escape From a Chinese Room. 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 (...)
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  11. William J. Rapaport (2006). How Helen Keller Used Syntactic Semantics to Escape From a Chinese Room. 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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  12. William J. Rapaport (2005). CASTANEDA, Hector-Neri (1924–1991). 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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  13. William J. Rapaport (2005). In Defense of Contextual Vocabulary Acquisition: How to Do Things with Words in Context. 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. 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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  14. William J. Rapaport (2005). Philosophy of Computer Science. 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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  15. William J. Rapaport (2005). Philosophy of Computer Science : An Introductory Course Philosophy of Computer Science : An Introductory Course. 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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  16. William J. Rapaport, Review of The Turing Test: Verbal Behavior As the Hallmark of Intelligence. [REVIEW]
    Stuart M. Shieber’s name is well known to computational linguists for his research and to computer scientists more generally for his debate on the Loebner Turing Test competition, which appeared a decade earlier in Communications of the ACM (Shieber 1994a, 1994b; Loebner 1994).1 With this collection, I expect it to become equally well known to philosophers.
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  17. William J. Rapaport (2003). What Did You Mean by That? Misunderstanding, Negotiation, and Syntactic Semantics. 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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  18. William J. Rapaport (2003). What Is the “Context” for Contextual Vocabulary Acquisition? 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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  19. William J. Rapaport (2002). Holism, Conceptual-Role Semantics, and Syntactic Semantics. 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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  20. William J. Rapaport & Michael W. Kibby (2002). Contextual Vocabulary Acquisition: A Computational Theory and Educational Curriculum. 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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  21. William J. Rapaport (2000). How to Pass a Turing Test: Syntactic Semantics, Natural-Language Understanding, and First-Person Cognition. Journal of Logic, Language, and Information 9 (4):467-490.
    I advocate a theory of syntactic semantics as a way of understanding how computers can think (and how the Chinese-Room-Argument objection to the Turing Test can be overcome): (1) Semantics, considered as the study of relations between symbols and meanings, can be turned into syntax – a study of relations among symbols (including meanings) – and hence syntax (i.e., symbol manipulation) can suffice for the semantical enterprise (contra Searle). (2) Semantics, considered as the process of understanding one domain (by modeling (...)
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  22. William J. Rapaport (1999). Implementation Is Semantic Interpretation. The Monist 82 (1):109-130.
    What is the computational notion of "implementation"? It is not individuation, instantiation, reduction, or supervenience. It is, I suggest, semantic interpretation. The online version differs from the published version in being a bit longer and going into a bit more detail.
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  23. William J. Rapaport (1998). How Minds Can Be Computational Systems. Journal of Experimental and Theoretical Artificial Intelligence 10 (4):403-419.
    The proper treatment of computationalism, as the thesis that cognition is computable, is presented and defended. Some arguments of James H. Fetzer against computationalism are examined and found wanting, and his positive theory of minds as semiotic systems is shown to be consistent with computationalism. An objection is raised to an argument of Selmer Bringsjord against one strand of computationalism, namely, that Turing-Test± passing artifacts are persons, it is argued that, whether or not this objection holds, such artifacts will inevitably (...)
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  24. William J. Rapaport & Francesco Orilia (eds.) (1998). Thought, Language, and Ontology, Essays in Memory of Hector-Neri Castaneda. Kluwer.
    The late Hector-Neri Castañeda, the Mahlon Powell Professor of Philosophy at Indiana University, and founding editor of Noûs, has deeply influenced current analytic philosophy with diverse contributions, including guise theory, the theory of indicators and quasi-indicators, and the proposition/practition theory. This volume collects 15 papers--for the most part previously unpublished--in ontology, philosophy of language, cognitive science, and related areas by ex-students of Professor Castañeda, most of whom are now well-known researchers or even distinguished scholars. The authors share the conviction that (...)
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  25. William J. Rapaport, Stuart C. Shapiro & Janyce M. Wiebe (1997). Quasi‐Indexicals and Knowledge Reports. Cognitive Science 21 (1):63-107.
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  26. Mary Galbraith & William J. Rapaport (1995). Preface To: Where Does I Come From? Special Issue on Subjectivity and the Debate Over Computational Cognitive Science. Minds and Machines 5 (4):513-620.
  27. Mary Galbraith & William J. Rapaport (1995). Preface. Minds and Machines 5 (4):513-515.
  28. William J. Rapaport (1995). Understanding Understanding: Syntactic Semantics and Computational Cognition. 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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  29. William J. Rapaport (1993). Because Mere Calculating Isn't Thinking: Comments on Hauser's Why Isn't My Pocket Calculator a Thinking Thing?. Minds and Machines 3 (1):11-20.
  30. Stuart C. Shapiro & William J. Rapaport (1992). The SNePS Family. 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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  31. William J. Rapaport (1991). Meinong, Alexius; I: Meinongian Semantics. In Hans Burkhardt & Barry Smith (eds.), Handbook of Metaphysics and Ontology. Philosophia Verlag.
    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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  32. William J. Rapaport (1991). Predication, Fiction, and Artificial Intelligence. 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 <span class='Hi'>fiction</span>, using SNePS. We briefly survey four philosophical ontological theories of <span class='Hi'>fiction</span> and sketch an epistemological theory (...)
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  33. William J. Rapaport (1991). The Inner Mind and the Outer World: Guest Editor's Introduction to a Special Issue on Cognitive Science and Artificial Intelligence. 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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  34. Stuart C. Shapiro & William J. Rapaport (1991). Models and Minds. In Robert E. Cummins & John L. Pollock (eds.), Philosophy and AI. Cambridge: MIT Press. 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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  35. William J. Rapaport, Computer Processes and Virtual Persons: Comments on Cole's "Artificial Intelligence and Personal Identity".
    This is a draft of the written version of comments on a paper by David Cole, presented orally at the American Philosophical Association Central Division meeting in New Orleans, 27 April 1990. Following the written comments are 2 appendices: One contains a letter to Cole updating these comments. The other is the handout from the oral presentation.
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  36. William J. Rapaport (1988). [Omnibus Review]. Journal of Symbolic Logic 53 (2):669-670.
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  37. William J. Rapaport (1988). Review: Brian Cantwell Smith, Varieties of Self-Reference. [REVIEW] Journal of Symbolic Logic 53 (2):661-662.
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  38. William J. Rapaport (1988). Review: Cynthia Dwork, Yoram Moses, Knowledge and Common Knowledge in a Byzantine Environment I: Crash Failures. [REVIEW] Journal of Symbolic Logic 53 (2):666-666.
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  39. William J. Rapaport (1988). Review: Christophe Geissler, Kurt Konolige, A Resolution Method for Quantified Modal Logics of Knowledge and Belief. [REVIEW] Journal of Symbolic Logic 53 (2):668-668.
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  40. William J. Rapaport (1988). Review: Fred Landman, Pegs and Alecs. [REVIEW] Journal of Symbolic Logic 53 (2):662-663.
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  41. William J. Rapaport (1988). Review: Gerhard Lakemeyer, Steps Towards a First-Order Logic of Explicit and Implicit Belief. [REVIEW] Journal of Symbolic Logic 53 (2):668-668.
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  42. William J. Rapaport (1988). Review: Gordon Plotkin, Colin Stirling, A Framework for Intuitionistic Modal Logics. [REVIEW] Journal of Symbolic Logic 53 (2):669-669.
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  43. William J. Rapaport (1988). Review: Jim des Rivieres, Hector J. Levesque, The Consistency of Syntactical Treatments of Knowledge. [REVIEW] Journal of Symbolic Logic 53 (2):665-666.
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  44. William J. Rapaport (1988). Review: Jaakko Hintikka, Reasoning About Knowledge in Philosophy: The Paradigm of Epistemic Logic. [REVIEW] Journal of Symbolic Logic 53 (2):663-664.
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  45. William J. Rapaport (1988). Review: Joao P. Martins, Stuart C. Shapiro, Theoretical Foundations for Belief Revision. [REVIEW] Journal of Symbolic Logic 53 (2):669-669.
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  46. William J. Rapaport (1988). Review: Joseph Y. Halpern, Reasoning About Knowledge: An Overview. [REVIEW] Journal of Symbolic Logic 53 (2):660-661.
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  47. William J. Rapaport (1988). Review: Kurt Konolige, What Awareness Isn't: A Sentential View of Implicit and Explicit Belief. [REVIEW] Journal of Symbolic Logic 53 (2):667-668.
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  48. William J. Rapaport (1988). Review: Leora Morgenstern, A First Order Theory of Planning, Knowledge, and Action. [REVIEW] Journal of Symbolic Logic 53 (2):664-665.
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  49. William J. Rapaport (1988). Review: Moshe Y. Vardi, On Epistemic Logic and Logical Omniscience. [REVIEW] Journal of Symbolic Logic 53 (2):668-668.
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  50. William J. Rapaport (1988). Review: Nicholas M. Asher, Johan A. W. Kamp, The Knower's Paradox and Representational Theories of Attitudes. [REVIEW] Journal of Symbolic Logic 53 (2):666-666.
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  51. William J. Rapaport (1988). Review: Richard E. Ladner, John H. Reif, The Logic of Distributed Protocols (Preliminary Report). [REVIEW] Journal of Symbolic Logic 53 (2):667-667.
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  52. William J. Rapaport (1988). Review: Ronald Fagin, Moshe Y. Vardi, Knowledge and Implicit Knowledge in a Distributed Environment: Preliminary Report. [REVIEW] Journal of Symbolic Logic 53 (2):667-667.
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  53. William J. Rapaport (1988). Review: Richmond H. Thomason, Paradoxes and Semantic Representation. [REVIEW] Journal of Symbolic Logic 53 (2):667-667.
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  54. William J. Rapaport (1988). Review: Raymond M. Smullyan, Logicians Who Reason About Themselves. [REVIEW] Journal of Symbolic Logic 53 (2):668-669.
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  55. William J. Rapaport (1988). Review: Stanley J. Rosenschein, Leslie Pack Kaelbling, The Synthesis of Digital Machines with Provable Epistemic Properties. [REVIEW] Journal of Symbolic Logic 53 (2):664-664.
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  56. William J. Rapaport (1988). Syntactic Semantics: Foundations of Computational Natural Language Understanding. In James H. Fetzer (ed.), Aspects of AI. Kluwer.
    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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  57. William J. Rapaport (1988). To Think or Not to Think. Noûs 22 (4):585-6098.
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  58. Janyce M. Wiebe & William J. Rapaport (1988). A Computational Theory of Perspective and Reference in Narrative. In Proceedings of the 26th Annual Meeting of the Association for Computational Linguistics. Association 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'.
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  59. Janyce M. Wiebe & William J. Rapaport (1988). A Computational Theory of Perspective and Reference in Narrative. In Proceedings of the 26th Annual Meeting of the Association 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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  60. Janyce M. Wiebe & William J. Rapaport (1988). Proceedings of the 26th Annual Meeting of the Association for Computational Linguistics.
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  61. William J. Rapaport (1987). Philosophy for Children and Other People. 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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  62. W. Rapaport (1986). Logical Foundations for Belief Representation. Cognitive Science 10 (4):371-422.
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  63. William J. Rapaport (1986). Philosophy of Artificial Intelligence: A Course Outline. 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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  64. William J. Rapaport (1986). Ethical Issues in the Use of Computers. Teaching Philosophy 9 (3):275-278.
  65. William J. Rapaport (1986). Logical Foundations for Belief Representation. Cognitive Science 422 (4):371-422.
    \nThis essay presents a philosophical and computational theory of the representation.
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  66. William J. Rapaport (1986). 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] Journal of Symbolic Logic 51 (1):248-252.
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  67. William J. Rapaport (1986). Searle's Experiments with Thought. Philosophy of Science 53 (June):271-9.
    A critique of several recent objections to John Searle's Chinese-Room Argument against the possibility of "strong AI" is presented. The objections are found to miss the point, and a stronger argument against Searle is presented, based on a distinction between "syntactic" and "semantic" understanding.
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  68. William J. Rapaport (1985). To Be and Not to Be. Noûs 19 (2):255-271.
    Terence Parsons's informal theory of intentional objects, their properties, and modes of predication does not adequately reflect ordinary ways of speaking and thinking. Meinongian theories recognizing two modes of predication are defended against Parsons's theory of two kinds of properties. Against Parsons's theory of fictional objects, I argue that no existing entities appear in works of fiction. A formal version of Parsons's theory is presented, and a curious consequence about modes of predication is indicated.
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  69. William J. Rapaport (1982). Meinong, Defective Objects, and (Psycho-)Logical Paradox. Grazer Philosophische Studien 18:17-39.
    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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  70. William J. Rapaport (1982). Unsolvable Problems and Philosophical Progress. American Philosophical Quarterly 19 (4):289 - 298.
    Philosophy has been characterized (e.g., by Benson Mates) as a field whose problems are unsolvable. This has often been taken to mean that there can be no progress in philosophy as there is in mathematics or science. The nature of problems and solutions is considered, and it is argued that solutions are always parts of theories, hence that acceptance of a solution requires commitment to a theory (as suggested by William Perry's scheme of cognitive development). Progress can be had in (...)
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  71. William Rapaport (1979). Errata: Meinongian Theories and a Russellian Paradox. Noûs 13 (1):125.
    List of errata to Rapaport, William J. (1978), "Meinongian Theories and a Russellian Paradox", Noûs 12: 153-180.
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  72. William J. Rapaport (1979). An Adverbial Meinongian Theory. Analysis 39 (March):75-81.
    A fundamental assumption of Alexius Meinong's 1904 Theory of Objects is the act-content-object analysis of psychological experiences. I suggest that Meinong's theory need not be based on this analysis, but that an adverbial theory might suffice. I then defend the adverbial alternative against an objection raised by Roderick Chisholm, and conclude by presenting an apparently more serious objection based on a paradox discovered by Romane Clark.
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  73. William J. Rapaport (1978). Meinongian Theories and a Russellian Paradox. Noûs 12 (2):153-180.
    This essay re-examines Meinong's "Über Gegenstandstheorie" and undertakes a clarification and revision of it that is faithful to Meinong, overcomes the various objections to his theory, and is capable of offering solutions to various problems in philosophy of mind and philosophy of language. I then turn to a discussion of a historically and technically interesting Russell-style paradox (now known as "Clark's Paradox") that arises in the modified theory. I also examine the alternative Meinong-inspired theories of Hector-Neri Castañeda and Terence Parsons.
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  74. William J. Rapaport (1976). On Cogito Propositions. 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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