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Titlebook: Discovery Science; Third International Setsuo Arikawa,Shinichi Morishita Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 200

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Discovery and Deduction one of learning from positive data, and the notion of ., which is commonly recognized in learning from positive data, is introduced into iterative computation of loop in- variants. The similarity between the widening operator in abstract inter- pretation and Gold’s notion of identification in the limit is also discussed.
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Language Learning with a Neighbor Systemrantee. In this paper, we allow an inference machine to infer a neighbor closure instead of the orig- inal language as an admissible approximation. We formalize such kind of inference, and give some sufficient conditions for a hypothesis space.
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Prologue: The Medieval Atlantic Ocean of items. These notes were written for CS345 at Stanford University and are reprinted by permission of the author. http://www-db.stanford.edu/~ullman/mining/mining.html gives you access to the entire set of notes, including additional citations and on-line links.
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Human Discovery Processes Based on Searching Experiments in Virtual Psychological Research Environmeulator in which subjects try to generate hypotheses and conduct experiments as scientists do. We analyze the subjects’ behavior based on SES and discuss the relation between the characteristics of their behavior and their performance of discovering targets.
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Probability Concepts in Quantum Mechanicsf this fraction as N goes to infinity. In many cases that arise in practice, the answers we get using this method can be shown to match heuristic assumptions made in many standard AI systems. I also show that when the language is restricted to unary predicates (for example, symptoms and diseases, bu
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