@inproceedings{janikow:2003:ANNIE,
title = {Adaptation of Representation in Genetic Programming},
author = {Cezary Z. Janikow and Rahul A Deshpande},
booktitle = {Smart Engineering System Design: Neural Networks,
Fuzzy Logic, Evolutionary Programming, Complex Systems,
and Artificial Life (ANNIE'2003)},
editor = {Cihan H. Dagli and Anna L. Buczak and Joydeep Ghosh and Mark J. Embrechts and Okan Ersoy},
month = {2-5 November},
pages = {45--50},
publisher = {ASME Press},
year = {2003},
abstract = {This paper discusses our initial work on automatically
adapting Genetic Programming (GP) representation. We
present here two independent techniques: AMS and ACE.
Both techniques are based on Constrained GP (CGP),
which uses mutation set methodology to prune the
representation space according to some context-specific
constraints. The ASM technique monitors the performance
of local context heuristics when used in
mutation/crossover, during GP evolution, and
dynamically modifies the heuristics. The ACE technique
iterates complete CGP runs and then uses the
distribution information from the best solutions to
adjust the heuristics for the next iteration. As the
results indicate, GP is able to gain substantial
performance improvements as well as learn qualitative
heuristics.},
keywords = {algorithms, genetic programming }
}
::