Nonparametric neighborhood methods for learning entail estimation of class conditional probabilities based on relative frequencies of samples that are "near-neighbors" of...
This paper considers the model of Time Petri Nets (TPNs) extended with time parameters and its use to perform on-line diagnosis of distributed systems. We propose to base the metho...
Bartosz Grabiec, Louis-Marie Traonouez, Claude Jar...
This paper presents a method to induce relational concepts with neural networks using the inductive logic programming system LINUS. Some first-order inductive learning tasks taken...
Rodrigo Basilio, Gerson Zaverucha, Artur S. d'Avil...
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...