Communications of the ACM
Elements of information theory
Elements of information theory
C4.5: programs for machine learning
C4.5: programs for machine learning
The nature of statistical learning theory
The nature of statistical learning theory
Knowledge compilation and theory approximation
Journal of the ACM (JACM)
Machine Learning
A Cellular Neural Associative Array for Symbolic Vision
Hybrid Neural Systems, revised papers from a workshop
Cognitive Systems Research
Drawing attention to the dangerous
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
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We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advance. We split the building of the hypothesis in various levels of increasing description complexity according to additional inductive biases received at run time. In order to give semantic value to the learnt formulas, the key operational aspect represented is the understandability of formulas, which requires their simplification at any level of description. We deepen this aspect in light of two alternative simplification methods, which we compare through a case study.