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» Knowledge Representation with Logic Programs
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ICTAI
2007
IEEE
14 years 3 months ago
ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming
In this paper we developed an Inductive Logic Programming (ILP) based framework ExOpaque that is able to extract a set of Horn clauses from an arbitrary opaque machine learning mo...
Yunsong Guo, Bart Selman
ICLP
2010
Springer
14 years 5 days ago
Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
Daan Fierens
ILP
2004
Springer
14 years 2 months ago
On Avoiding Redundancy in Inductive Logic Programming
ILP systems induce first-order clausal theories performing a search through very large hypotheses spaces containing redundant hypotheses. The generation of redundant hypotheses ma...
Nuno A. Fonseca, Vítor Santos Costa, Fernan...
AI
2001
Springer
14 years 1 months ago
Knowledge and Planning in an Action-Based Multi-agent Framework: A Case Study
The situation calculus is a logical formalism that has been extensively developed for planning. We apply the formalism in a complex multi-agent domain, modelled on the game of Clue...
Bradley Bart, James P. Delgrande, Oliver Schulte
AMAI
2004
Springer
14 years 2 months ago
Production Inference, Nonmonotonicity and Abduction
We introduce a general formalism of production inference relations that posses both a standard monotonic semantics and a natural nonmonotonic semantics. The resulting nonmonotonic...
Alexander Bochman