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Abstract: . This paper describes a representation framework, that offers a unifying platform for alternative systems, which learn concepts in First Order Logic. The main aspects of this framework are discussed. First of all, the separation between the hypothesis logical language (a version of the V L21 language) and the representation of data by means of a relational database is motivated. Then, the functional layer between data and hypotheses, which makes the data accessible by the logical level... (Update)
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...as fixed length bitstrings. A detailed description of the language used by G NET can be found in (Giordana and Neri, 1996; Giordana et al. 1997). G NET s inductive engine exploits a stochastic algorithm organized in two levels. The lower level, named Genetic layer (G layer)...
.... by adjusting parameters for reaching G when confronted to other individual goals Techniques Relational learning (Aha, 1992 ; Giordana et al. 1997; Muggleton and Raedt, 1994; Zucker et al. 1998) Concept learning (Dietterich 1990) Difficulties The expressive power of IDL, the...
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BibTeX entry: (Update)
Giordana, A., Neri, F., Saitta, L., and Botta, M. (1997). Integrating multiple learning strategies in first order logics. Machine Learning, pages 209-- 240. http://citeseer.ist.psu.edu/giordana97integrating.html More
@article{ giordana97integrating,
author = "Attilio Giordana and Filippo Neri and Lorenza Saitta and Marco Botta",
title = "Integrating Multiple Learning Strategies in First Order Logics",
journal = "Machine Learning",
volume = "27",
number = "3",
pages = "209-240",
year = "1997",
url = "citeseer.ist.psu.edu/giordana97integrating.html" }
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