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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 ...
SEMWEB
2009
Springer
15 years 6 months ago
An Algorithm for Learning with Probabilistic Description Logics
Probabilistic Description Logics are the basis of ontologies in the Semantic Web. Knowledge representation and reasoning for these logics have been extensively explored in the last...
José Eduardo Ochoa Luna, Fabio Gagliardi Co...
AMAST
2010
Springer
14 years 6 months ago
Learning in a Changing World, an Algebraic Modal Logical Approach
Abstract. We develop an algebraic modal logic that combines epistemic and dynamic modalities with a view to modelling information acquisition (learning) by automated agents in a ch...
Prakash Panangaden, Mehrnoosh Sadrzadeh
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
IUI
1999
ACM
15 years 4 months ago
Programming by Demonstration: An Inductive Learning Formulation
Although Programming by Demonstration (PBD) has the potential to improve the productivity of unsophisticated users, previous PBD systems have used brittle, heuristic, domain-speci...
Tessa A. Lau, Daniel S. Weld