Titlebook: Algorithmic Learning for Knowledge-Based Systems; GOSLER Final Report Klaus P. Jantke,Steffen Lange Book 1995 Springer-Verlag Berlin Heidel

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Der Buchungsschlüssel für Industriebetriebeconsistent and conservative, though not in general strong monotonic. This class of languages has neither of the properties of finite thickness and finite elasticity usually used to prove inferability from positive data, so our proof method is the explicit construction of a tell-tale function for the

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https://doi.org/10.1007/978-3-476-03346-8ng set-theoretic concepts and logical functions..Many concepts of knowledge-based problem-solving are incorporated into one system which has been based on set-theoretical concepts. This results in a consisting methodology and in a comprehensive set of tools applicable in many fields. The transition

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https://doi.org/10.1007/3-540-60217-8Algorithmic Learning; Formal Languages; Indcutive Inference; Induktives Schlie?en; Machine Learning; Wiss

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Learning and consistency,tly and completely reflected in the hypothesis the algorithm outputs on these data. However, this approach may totally fail. It may lead to the unsolvability of the learning problem, or it may exclude any efficient solution of it..Therefore we study several types of consistent learning in recursion-

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Error detecting in inductive inference,n so far. This notion is made mathematically precise and its general power is characterized. In spite of its strength it is shown that this approach is not of universal power. Consequently, then hypotheses are considered which “unprovably misclassify” examples and the properties of this approach are