Heuristic Learning based on Genetic Programming
Genetic Programming, Proceedings of EuroGP'2001, volume 2038 of LNCS, page 1--10. Lake Como, Italy, Springer-Verlag, (18-20 April 2001)Abstract
In this paper we present an approach to learning
heuristics based on Genetic Programming (GP). Instead
of directly solving the problem by application of GP,
GP is used to develop a heuristic that is applied to
the problem instance. By this, the typical large
runtimes of evolutionary methods have to be invested
only once in the learning phase. The resulting
heuristic is very fast. The technique is applied to a
field from the area of VLSI CAD, i.e. minimization of
Binary Decision Diagrams (BDDs). We chose this topic
due to its high practical relevance and since it
matches the criteria where our algorithm works best,
i.e. large problem instances where standard
evolutionary techniques cannot be applied due to their
large runtimes. Our experiments show that we obtain
high quality results that outperform previous methods,
while keeping the advantage of low runtimes.