%0 Conference Paper %1 sarafopoulos:2001:EuroGP %A Sarafopoulos, Anargyros %B Genetic Programming, Proceedings of EuroGP'2001 %C Lake Como, Italy %D 2001 %E Miller, Julian F. %E Tomassini, Marco %E Lanzi, Pier Luca %E Ryan, Conor %E Tettamanzi, Andrea G. B. %E Langdon, William B. %I Springer-Verlag %K Evolution Function GP, Iterated STGP, Strategies, Strongly Systems Typed algorithms, genetic programming, %P 176--191 %T Evolution of Affine Transformations and Iterated Function Systems using Hierarchical Evolution Strategy %U http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=176 %V 2038 %X Often optimization problems involve the discovery of many scalar coefficients. Although genetic programming (GP) has been applied to the optimization and discovery of functions with an arbitrary number of scalar coefficients, recent results indicate that a method for fine-tuning GP scalar terminals can assist the discovery of solutions. In this paper we demonstrate an approach where genetic programming and evolution strategies (ES) are seamlessly combined. We apply our GP/ES hybrid, which we name Hierarchical Evolution Strategy, to the problem of evolving affine transformations and iterated function systems (IFS). We compare the results of our approach with GP and notice an improvement in performance in terms of discovering better solutions and speed. %@ 3-540-41899-7

@inproceedings{sarafopoulos:2001:EuroGP, abstract = {Often optimization problems involve the discovery of many scalar coefficients. Although genetic programming (GP) has been applied to the optimization and discovery of functions with an arbitrary number of scalar coefficients, recent results indicate that a method for fine-tuning GP scalar terminals can assist the discovery of solutions. In this paper we demonstrate an approach where genetic programming and evolution strategies (ES) are seamlessly combined. We apply our GP/ES hybrid, which we name Hierarchical Evolution Strategy, to the problem of evolving affine transformations and iterated function systems (IFS). We compare the results of our approach with GP and notice an improvement in performance in terms of discovering better solutions and speed.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Lake Como, Italy}, author = {Sarafopoulos, Anargyros}, biburl = {https://www.bibsonomy.org/bibtex/287eacc0a6d7d77e594a96e4180898faa/brazovayeye}, booktitle = {Genetic Programming, Proceedings of EuroGP'2001}, editor = {Miller, Julian F. and Tomassini, Marco and Lanzi, Pier Luca and Ryan, Conor and Tettamanzi, Andrea G. B. and Langdon, William B.}, interhash = {9659e5c0ed9b699d91803b643e799a1d}, intrahash = {87eacc0a6d7d77e594a96e4180898faa}, isbn = {3-540-41899-7}, keywords = {Evolution Function GP, Iterated STGP, Strategies, Strongly Systems Typed algorithms, genetic programming,}, month = {18-20 April}, notes = {EuroGP'2001, part of miller:2001:gp. Best student paper}, organisation = {EvoNET}, pages = {176--191}, publisher = {Springer-Verlag}, publisher_address = {Berlin}, series = {LNCS}, size = {16 pages}, timestamp = {2008-06-19T17:51:03.000+0200}, title = {Evolution of Affine Transformations and Iterated Function Systems using Hierarchical Evolution Strategy}, url = {http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=176}, volume = 2038, year = 2001 }