This paper aims at presenting the application of first-order logic machine learning techniques to two document domains in order to learn rules for recognizing the semantic role of...
Stefano Ferilli, Nicola Di Mauro, Teresa Maria Alt...
-- An approach to estimate the number of rules by spectral analysis of the training dataset has been recently proposed [1]. This work presents an analysis of such a method in high ...
Vinicius da F. Vieira, Alexandre Evsukoff, Beatriz...
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Abstract. This paper describe the implementation and underlying philosophie of a large scale distributed computation of K-optimal lattice rules. The computation is huge correspondi...
Run-time monitoring of temporal properties and assertions is used for testing and as a component of execution-based model checking techniques. Traditional run-time monitoring howev...