143 search results - page 7 / 29 » On Using Machine Learning for Logic BIST |
ICMLA
2009
13 years 5 months ago
2009
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
IEAAIE
2004
Springer
14 years 25 days ago
2004
Springer
The main issue in e-learning is student modelling, i.e. the analysis of a student’s behaviour and prediction of his/her future behaviour and learning performance. Indeed, it is d...
ICMLA
2010
13 years 4 months ago
2010
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...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. Learning ML...