Machine Learning and Natural Language Processing Lab

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Student's Project

Learning from Greedy SAT

Christian Stolle, 2003

Learning from satisfiability combines learning from entailment with learning from interpretations. As such it is a formalisation of concept-learning. The good practical results of GSAT as aSAT-solver led to the combination of GSAT with learning from satisfiability. This work discusses some implementational issues of learning from satisfiability and comparing it with other CNF learners and its combination with GSAT.