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  1. An assumption-based TMS.Johan de Kleer - 1986 - Artificial Intelligence 28 (2):127-162.
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  • Motivation analysis, abductive unification, and nonmonotonic equality.Eugene Charniak - 1988 - Artificial Intelligence 34 (3):275-295.
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  • Imputations and Explications: Representational Problems in Treatments of Prepositional Attitudes.John A. Barnden - 1986 - Cognitive Science 10 (3):319-364.
    The representation of propositional attitudes (beliefs, desires, etc.) and the analysis of natural-language, propositional-attitude reports presents difficult problems for cognitive science and artificial intelligence. In particular, various representational approaches to attitudes involve the incorrect “imputation,” to cognitive agents, of the use of artificial theory-laden notions. Interesting cases of this problem are shown to occur in several approaches to attitudes. The imputation problem is shown to arise from the way that representational approaches explicate properties and relationships, and in particular from the (...)
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  • Some Philosophical Problems from the Standpoint of Artificial Intelligence.J. McCarthy & P. J. Hayes - 1969 - Machine Intelligence 4:463-502.
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  • Logical foundations for belief representation.William J. 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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  • Quantifiers and propositional attitudes.Willard van Orman Quine - 1955 - Journal of Philosophy 53 (5):177-187.
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  • Languages with self-reference I: Foundations.Donald Perlis - 1985 - Artificial Intelligence 25 (3):301-322.
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  • Tarskian semantics, or no notation without denotation.Drew McDermott - 1978 - Cognitive Science 2 (3):277-82.
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  • Intensional Concepts in Propositional Semantic Networks.Anthony S. Maida & Stuart C. Shapiro - 1982 - Cognitive Science 6 (4):291-330.
    An integrated statement is made concerning the semantic status of nodes in a propositional semantic network, claiming that such nodes represent only intensions. Within the network, the only reference to extensionality is via a mechanism to assert that two intensions have the same extension in same world. This framework is employed in three application problems to illustrate the nature of its solutions.The formalism used here utilizes only assertional information and no structural, or definitional, information. This restriction corresponds to many of (...)
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  • Counterpart theory and quantified modal logic.David Lewis - 1968 - Journal of Philosophy 65 (5):113-126.
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  • Quantifying in.David Kaplan - 1968 - Synthese 19 (1-2):178-214.
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  • A syntactic theory of belief and action.Andrew R. Haas - 1986 - Artificial Intelligence 28 (3):245-292.
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  • Reference and definite descriptions.Keith S. Donnellan - 1966 - Philosophical Review 75 (3):281-304.
    Definite descriptions, I shall argue, have two possible functions. 1] They are used to refer to what a speaker wishes to talk about, but they are also used quite differently. Moreover, a definite description occurring in one and the same sentence may, on different occasions of its use, function in either way. The failure to deal with this duality of function obscures the genuine referring use of definite descriptions. The best known theories of definite descriptions, those of Russell and Strawson, (...)
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  • Mental Spaces from a Functional Perspective.John Dinsmore - 1987 - Cognitive Science 11 (1):1-21.
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