%0 Conference Paper %1 luke:1999:P %A Luke, Sean %A Hamahashi, Shugo %A Kitano, Hiroaki %B Proceedings of the Genetic and Evolutionary Computation Conference %C Orlando, Florida, USA %D 1999 %E Banzhaf, Wolfgang %E Daida, Jason %E Eiben, Agoston E. %E Garzon, Max H. %E Honavar, Vasant %E Jakiela, Mark %E Smith, Robert E. %I Morgan Kaufmann %K algorithms, and evolvable genetic hardware programming %P 1098--1105 %T ``Genetic'' Programming %U http://www.cs.gmu.edu/~sean/papers/gene-gecco99.ps.gz %V 2 %X Much of evolutionary computation was inspired by Mendelian genetics. But modern genetics has since advanced considerably, revealing that genes are not simply parameter settings, but interactive cogs in a complex chemical machine. At the same time, an increasing number of evolutionary computation domains are evolving non-parameterized mechanisms such as neural networks or symbolic computer programs. As such, we think modern biological genetics offers much in helping us understand how to evolve such things. In this paper, we present a gene regulation model for Drosophila melanogaster. We then apply gene regulation to evolve deterministic finite-state automata, and show that our approach does well compared to past examples from the literature. %@ 1-55860-611-4

@inproceedings{luke:1999:P, abstract = {Much of evolutionary computation was inspired by Mendelian genetics. But modern genetics has since advanced considerably, revealing that genes are not simply parameter settings, but interactive cogs in a complex chemical machine. At the same time, an increasing number of evolutionary computation domains are evolving non-parameterized mechanisms such as neural networks or symbolic computer programs. As such, we think modern biological genetics offers much in helping us understand how to evolve such things. In this paper, we present a gene regulation model for Drosophila melanogaster. We then apply gene regulation to evolve deterministic finite-state automata, and show that our approach does well compared to past examples from the literature.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Orlando, Florida, USA}, author = {Luke, Sean and Hamahashi, Shugo and Kitano, Hiroaki}, biburl = {https://www.bibsonomy.org/bibtex/2fa887155ea5ef6a840dee4616cf77b09/brazovayeye}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference}, editor = {Banzhaf, Wolfgang and Daida, Jason and Eiben, Agoston E. and Garzon, Max H. and Honavar, Vasant and Jakiela, Mark and Smith, Robert E.}, interhash = {a36bd7cee9576198980c46da349a2b7a}, intrahash = {fa887155ea5ef6a840dee4616cf77b09}, isbn = {1-55860-611-4}, keywords = {algorithms, and evolvable genetic hardware programming}, month = {13-17 July}, notes = {GECCO-99 A joint meeting of the eighth international conference on genetic algorithms (ICGA-99) and the fourth annual genetic programming conference (GP-99)}, pages = {1098--1105}, publisher = {Morgan Kaufmann}, publisher_address = {San Francisco, CA 94104, USA}, timestamp = {2008-06-19T17:45:57.000+0200}, title = {``Genetic'' Programming}, url = {http://www.cs.gmu.edu/~sean/papers/gene-gecco99.ps.gz}, volume = 2, year = 1999 }