keywords = "genetic algorithms, genetic programming, building
blocks, frequent subtree mining, probabilistic model
building genetic programming",
abstract = "One crucial issue in genetic programming (GP) is how
to acquire promising building blocks efficiently. In
this paper, we propose a GP method (called GPTM, GP
with Tree Mining) which protects the subtrees
repeatedly appearing in superior individuals. Currently
GPTM uses a FREQT-like efficient data mining method to
find such subtrees. GPTM is evaluated by three
benchmark problems, and the results indicate that GPTM
is comparable to or better than POLE, one of the most
advanced probabilistic model building GP methods, and
finds the optimal individual earlier than the standard
GP and POLE.",
notes = "GECCO-2008 A joint meeting of the seventeenth
international conference on genetic algorithms
(ICGA-2008) and the thirteenth annual genetic
programming conference (GP-2008).
ACM Order Number 910081. Also known as
\cite{1389332}