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Multiple Predicate Learning with RTL (1995)  (Make Corrections)  (2 citations)
Cristina Baroglio, Marco Botta
Topics in Artificial Intelligence



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Abstract: . RTL is an algorithm designed to learn any number of simple, mutually dependent relations, producing recursive programs that are stratified in the sense given by Apt. In this paper, we present a revised algorithm and its implementation based on previous theoretical works that establish properties and limits of the learning framework. The algorithm is described both in abstract form and through an example. Emphasis is put on the way RTL uses induction and domain knowledge to guide the... (Update)

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.... learning systems can easily be extended in order to learn recursive concepts, as in the system RTL (Giordana et al. 1993a; Baroglio and Botta, 1995); on the other hand, such an extension may not be so easy for other systems, as shown in (Cameron Jones and Quinlan, 1993)...

.... and Limitations There are some ILP systems that are able to learn multi class concepts represented in first order rules, such as RTL [1], ICL[7] MULT ICN[9] Nevertheless, it is still possible that some unseen data may not exactly match the rules produced by these systems....

Cited by:   More
Approximate ILP Rules by Backpropagation Neural Network.. - Kijsirikul, Sinthupinyo (1999)   (Correct)
Integrating Multiple Learning Strategies in First Order Logics - Giordana, Neri, al. (1997)   (Correct)

Active bibliography (related documents):   More   All
0.5:   Learning First Order Theories - Botta (1994)   (Correct)
0.3:   Inductive Logic Programming: Theory And Methods - Muggleton, De Raedt (1994)   (Correct)
0.3:   Architecture for Iterative Learning of Recursive Definitions - Jorge, Brazdil (1996)   (Correct)

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0.4:   Relational Learning as Search in a Critical Region - Botta, Giordana, Saitta.. (2003)   (Correct)
0.3:   Discovering Complex Events in Long Sequences - Marco Botta Botta   (Correct)
0.3:   Learning in the 'Real World' - Saitta, Neri (1998)   (Correct)

BibTeX entry:   (Update)

Baroglio, C. and Botta, M. (1995). Multiple predicate learning with RTL. In 4th Congress of the Italian Association for Artificial Intelligence AI*IA'95, pages 44--55, Florence, Italy. http://citeseer.ist.psu.edu/baroglio95multiple.html   More

@inproceedings{ botta95multiple,
    author = "C. Baroglio \and M. Botta",
    title = "Multiple Predicate Learning with {RTL}",
    booktitle = "Topics in Artificial Intelligence",
    volume = "LNAI 992",
    publisher = "Springer",
    editor = "M. Gori and G. Soda",
    year = "1995",
    url = "citeseer.ist.psu.edu/baroglio95multiple.html" }
Citations (may not include all citations):
435   Towards a Theory of Declarative Knowledge (context) - Apt, Blair et al. - 1988
3   Learning Mutually Dependent Relations (context) - Baroglio, Giordana et al. - 1992
2   Learning First Order Theories - Botta - 1994
2   SMART+: A Multi-Strategy Learning Tool (context) - Botta, Giordana - 1993

Documents on the same site (http://www.di.unito.it/~mluser/SELECTbib.html):
FONN: Combining First Order Logic with Connectionist Learning - Botta, Giordana, Piola (1997)   (Correct)

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