William J. Rapaport

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 grading, grading on a curve, and the subjectivity of grading) are discussed

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.

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 classroom curriculum designed to help students use CVA to improve their reading comprehension.

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 to Rapaport. One family of paradoxes remains, but it is argued that they are unavoidable and relatively harmless.

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 makes sense. The question is: What sense does it make?" This essay explores what sense it makes to say that syntax by itself is sufficient for semantics.

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 it) in terms of another, can be viewed recursively: The base case of semantic understanding –understanding a domain in terms of itself – is syntactic understanding. (3) An internal (or narrow ), first-person point of view makes an external (or wide ), third-person point of view otiose for purposes of understanding cognition

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 a prototype natural-language-understanding system is presented as an illustration.

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 in a public communication language and in a knowledge-representation language, we demonstrate the importance of representing proper names explicitly, and we provide support for the necessity of considering sentences in the context of extended discourse (for example, written narrative) in order to fully capture certain features of their semantics.

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 as objects of beliefs. These requirements raise questions about the number of tokens of the belief representation language needed to represent believers and propositions in their normal roles and in their roles as objects of beliefs. In this paper, we explicate the relations among nodes, mental tokens, concepts, actual objects, concepts in the belief spaces of an agent and the agent's model of other agents, concepts of other cognitive agents, and propositions. We extend, deepen, and clarify our theory of intensional knowledge representation for natural-language processing, as presented in previous papers and in light of objections raised by others. The essential claim is that tokens in a knowledge-representation system represent only intensions and not extensions. We are pursuing this investigation by building CASSIE, a computer model of a cognitive agent and, to the extent she works, a cognitive agent herself. CASSIE's mind is implemented in the SNePS knowledge-representation and reasoning system.

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 embedding sentence. Therefore, the referent of the quasi-indicator must be represented in such a way that no invalid coreferential claims are entailed. The importance of quasi-indicators is discussed, and it is shown that all four of the above categories of belief reports can be handled by a single representational technique using belief spaces containing intensional entities. Inference rules and belief-revision techniques for the system are also examined.

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 Castañeda's work must continue to be explored and that his philosophical methodology must continue to be applied in an effort to further illuminate all the issues that he so deeply investigated. The topics covered by the contributions include intensional contexts, possible worlds, quasi-indicators, guise theory, property theory, Russell's substitutional theory of propositions, event theory, the adverbial theory of mental attitudes, existentialist ontology, and Plato's, Leibniz's, Kant's, and Peirce's ontologies. An introduction by the editors relates all these themes to Castañeda's philosophical interests and methodology.

Hauser argues that his pocket calculator (Cal) has certain arithmetical abilities: it seems Cal calculates. That calculating is thinking seems equally untendentious. Yet these two claims together provide premises for a seemingly valid syllogism whose conclusion - Cal thinks - most would deny. He considers several ways to avoid this conclusion, and finds them mostly wanting. Either we ourselves can't be said to think or calculate if our calculation-like performances are judged by the standards proposed to rule out Cal; or the standards- e.g., autonomy and self-consciousness- make it impossible to verify whether anything or anyone (save oneself) meets them. While appeals to the intentionality of thought or the unity of minds provide more credible lines of resistance, available accounts of intentionality and mental unity are insufficiently clear and warranted to provide very substantial arguments against Cal's title to be called a thinking thing. Indeed, considerations favoring granting that title are more formidable than is generally appreciated. Rapaport's comments suggest that, on a strong view of thinking, mere calculating is not thinking (and pocket calculators don't think), but on a weak, but unexciting, sense of thinking, pocket calculators do think. He closes with some observations on the implications of this conclusion.