Michael Lebowitz

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The generation of extended plots for melodramatic fiction is an interesting task for Artificial Intelligence research, one that requires the application of generalization techniques to carry out fully. UNIVERSE is a story-telling program that uses plan-like units, "plot fragments", to generate plot outlines. By using a rich library of plot fragments and a(More)
Extended story generation, such as the creation of soap opera stories, is a difficult and interesting problem for Artif icial Intelligence. We present here the first phase of the development of a program, UNIVERSE, to tell such stories. In particular, we introduce a method for creating universes of characters appropriate for extended story generation. This(More)
Lung cancer was found in 20 (9.8%) of 205 patients with cryptogenic fibrosing alveolitis (CFA) or 12.9% of the 155 patients in this series followed to death. An excess relative risk of lung cancer of 14.1 was found in patients with CFA compared to the general population of comparable age and sex, allowing for the lengths of follow-up of the CFA patients.(More)
Similarity-based learning, which invalves largely structural comparisons of instances, and explanation-based learning, a knowledge-intensive method far analyzing instances to build generalized schemata, are two major inductive learning techniques in use in Artificial Intelligence. In this paper, we propose a combination of the two methods-applying(More)
A new type of natural language parser is presented. The idea behind this parser is to map input sentences into the deepest form of the representation of their meaning and inferences, as is appropriate. The parser is not distinct from an entire understanding system. It uses an integrated conception of inferences, scripts, plans, and other knowledge to aid in(More)