Abstract
This paper investigates the influence of knowledge representation languages on the complexity of the learning process. However, the aim of the paper is not to give a state-of-the-art account of the involved issues, but to survey the underlying ideas. Then, references will be provided only occasionally and all the specific quantitative results are left to the presentation. Finally, the paper is intentionally unbalanced, because a larger space is given to those issues that are more novel or less investigated in the literature.
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© 1994 Springer-Verlag Berlin Heidelberg
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Neri, F., Saitta, L. (1994). Knowledge representation in machine learning. In: Bergadano, F., De Raedt, L. (eds) Machine Learning: ECML-94. ECML 1994. Lecture Notes in Computer Science, vol 784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57868-4_48
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DOI: https://doi.org/10.1007/3-540-57868-4_48
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