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Inductive Logic Programming [electronic resource] : 10th International Conference, ILP 2000 London, UK, July 24–27, 2000 Proceedings / edited by James Cussens, Alan Frisch.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Computer Science ; 1866Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2000Description: X, 262 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540449607
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TJ210.2-211.495
Online resources:
Contents:
Invited Paper -- ILP: Just Do It -- Contributed Papers -- A New Algorithm for Learning Range Restricted Horn Expressions -- A Refinement Operator for Description Logics -- Executing Query Packs in ILP -- A Logical Database Mining Query Language -- Induction of Recursive Theories in the Normal ILP Setting: Issues and Solutions -- Extending K-Means Clustering to First-Order Representations -- Theory Completion Using Inverse Entailment -- Solving Selection Problems Using Preference Relation Based on Bayesian Learning -- Concurrent Execution of Optimal Hypothesis Search for Inverse Entailment -- Using ILP to Improve Planning in Hierarchical Reinforcement Learning -- Towards Learning in CARIN-ALN -- Inverse Entailment in Nonmonotonic Logic Programs -- A Note on Two Simple Transformations for Improving the Efficiency of an ILP System -- Searching the Subsumption Lattice by a Genetic Algorithm -- New Conditions for the Existence of Least Generalizations under Relative Subsumption.
In: Springer eBooks
Item type: E-BOOKS
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IMSc Library Link to resource Available EBK5094

Invited Paper -- ILP: Just Do It -- Contributed Papers -- A New Algorithm for Learning Range Restricted Horn Expressions -- A Refinement Operator for Description Logics -- Executing Query Packs in ILP -- A Logical Database Mining Query Language -- Induction of Recursive Theories in the Normal ILP Setting: Issues and Solutions -- Extending K-Means Clustering to First-Order Representations -- Theory Completion Using Inverse Entailment -- Solving Selection Problems Using Preference Relation Based on Bayesian Learning -- Concurrent Execution of Optimal Hypothesis Search for Inverse Entailment -- Using ILP to Improve Planning in Hierarchical Reinforcement Learning -- Towards Learning in CARIN-ALN -- Inverse Entailment in Nonmonotonic Logic Programs -- A Note on Two Simple Transformations for Improving the Efficiency of an ILP System -- Searching the Subsumption Lattice by a Genetic Algorithm -- New Conditions for the Existence of Least Generalizations under Relative Subsumption.

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The Institute of Mathematical Sciences, Chennai, India