Using Previous Experience for Learning Planning Control Knowledge.
Susana Fernández, Ricardo Aler, Daniel Borrajo · 2004
Machine learning (ML) is often used to obtain control knowledge to improve planning efficiency. Usually, ML techniques are used in isolation from experience that could be obtained by other means. The aim of this pa-per is to determine experimentally the influence of us-ing such previous experience or prior knowledge (PK), so that the learning process is improved. In particu-lar, we study three different ways of getting such ex-perience: from a human, from another planner (called FF), and from a different ML technique. This previous experience has been supplied to two different ML tech-niques: a deductive-inductive system (hamlet) and a genetic-based one (evock).