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At the heart of natural language processing is the understanding of context dependent meanings. This paper presents a preliminary model of formal contexts based on situation theory. It also gives a worked-out example to show the use of contexts in lifting, i.e., how propositions holding in a particular context transform when they are moved to another context. This is useful in NLP applications where preserving meaning is a desideratum.

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If computational geometry should play an important role in the professional environment (e.g. graphics and robotics), the data structures it advocates should be readily implemented and the algorithms efficient. In the paper, the uniform grid and a diverse set of geometric algorithms that are all based on it, are reviewed. The technique, invented by the second author, is a flat, and thus non-hierarchical, grid whose resolution adapts to the data. It is especially suitable for telling efficiently which pairs of a large number of short edges intersect. Several of the algorithms presented here exist as working programs (among which is a visible surface program for polyhedra) and can handle large data sets (i.e. many thousands of geometric objects). Furthermore, the uniform grid is appropriate for parallel processing; the parallel implementation presented gives very good speed-up results. © 1989

This paper argues that in addition to the familiar approach using formal contexts, there is now a need in artificial intelligence to study contexts as social constructs. As a successful example of the latter approach, I draw attention to 'interpretation' (in the sense of literary theory), viz. the reconstruction of the intended meaning of a literary text that takes into account the context in which the author assumed the reader would place the text. An important contribution here comes from Wendell Harris, enumerating the seven crucial dimensions of context: knowledge of reality, knowledge of language, and the authorial, generic, collective, specific, and textual dimensions. Finally, two recent approaches to interpretation, due to Jon Barwise and Jerry Hobbs, are analyzed as useful attempts which also come to grips with the notion of context.It must be noted that there has been a considerable body of contributions connecting linguistic structure with social context. For example, anthropological linguistics, from Bronislaw Malinowski onwards, has underlined the cultural context of discourse as essential to meaning. This viewpoint became prominent with the emergence of the ethnography of speaking in anthropology. Thus, conversation analysis represents a consistent formal effort to contribute to an analysis of the nature of context. While this paper emphasizes and reviews the literary theory approach, it makes various contacts with works of the latter kind (e.g., the landmark contributions of Erving Goffman, John Gumperz, William Hanks, John Heritage, Dell Hymes, et al.) in order to deliver a more balanced and complete study of the dimensions of context.

Abstract. The Turing Test is one of the most disputed topics in artificial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing's ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the 'other minds' problem, and similar topics in philosophy of mind are discussed. We also cover the sociological and psychological aspects of the Turing Test. Finally, we look at the current situation and analyze programs that have been developed with the aim of passing the Turing Test. We conclude that the Turing Test has been, and will continue to be, an influential and controversial topic.