Sciweavers

53 search results - page 5 / 11
» A Logic Programming Framework for Learning by Imitation
Sort
View
CORR
2000
Springer
120views Education» more  CORR 2000»
14 years 11 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
CORR
2011
Springer
174views Education» more  CORR 2011»
14 years 3 months ago
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
Yoshitaka Kameya, Taisuke Sato
EUROCOLT
1999
Springer
15 years 3 months ago
Mind Change Complexity of Learning Logic Programs
The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds ...
Sanjay Jain, Arun Sharma
ICRA
2006
IEEE
149views Robotics» more  ICRA 2006»
15 years 5 months ago
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts
— This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
Sylvain Calinon, Florent Guenter, Aude Billard
ML
2006
ACM
122views Machine Learning» more  ML 2006»
14 years 11 months ago
PRL: A probabilistic relational language
In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
Lise Getoor, John Grant