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By P. Van Hentenryck, L. Michel, P. Laborie, W. Nuijten, J. Rogerie (auth.), Pedro Barahona, José J. Alferes (eds.)
The Portuguese organization for Arti cial Intelligence (APPIA) has been re- larly setting up the Portuguese convention on Arti cial Intelligence (EPIA). This 9th convention follows earlier ones held in Porto (1985), Lisboa (1986), Braga (1987), Lisboa (1989), Albufeira (1991), Porto (1993), Funchal (1995) and Coimbra (1997). beginning in 1989, the meetings were held biennially (alternating with an APPIA complicated tuition on Arti cial Intelligence) and develop into actually overseas: English has been followed because the o cial language and the complaints are released in Springer’s LNAI sequence. The convention has recon rmed its excessive foreign normal this 12 months, principally as a result of its programme committee, composed of amazing researchers in various specialities in Arti cial Intelligence, 1/2 them from Portuguese universities. This has attracted a signi cant foreign curiosity, good expressed by way of the variety of papers submitted (66), from 17 di erent nations, 29 of that are by means of Portuguese researchers. From the sixty six papers submitted, approximately one 3rd of them (23) have been chosen for oral presentation and feature been released during this quantity. The assessment approach enabled the choice of top of the range papers, every one paper being reviewed by way of or 3 reviewers, both from the programme committee or through their appointment. we wish to thank the entire reviewers for his or her very good and tough work.
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Besides the language bias, Tilde allows for lookahead and prepruning (according to the minimal number of examples covered) defined by parameter setting. First-order regression. , Xn are bound). Typical background knowledge predicates include less-or-equal tests, addition, subtraction and multiplication. An approach to relational regression is implemented in the system FORS (First Order Regression System) [33] which performs top-down search of a refinement graph. In each clause, FORS can predict a value for the target variable Y as the output value of a background knowledge literal, as a constant, or as a linear combination of variables appearing in the clause (using linear regression).
Machine Learning, 26(2/3): 147–176, 1997. 34. M. S. Subrahmanian. Generalized annotated logic programs. Journal of Logic Programming, 1992. 35. D. King, S. Muggleton, R. E. Sternberg. Drug design by machine learning: The use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase. Proc. of the National Academy of Sciences of the USA 89(23): 11322–11326, 1992. 36. M. Kirsten, S. Wrobel. Relational distance-based clustering.