%0 Thesis %1 gustafson:mastersthesis %A Gustafson, Steven M. %C Manhattan, KS, USA %D 2000 %K algorithms, genetic programming %T Layered learning in genetic programming for a co-operative robot soccer problem %U http://citeseer.ist.psu.edu/450396.html %X We present an alternative to standard genetic programming (GP) that applies layered learning techniques to decompose a problem. GP is applied to subproblems sequentially, where the population in the last generation of a subproblem is used as the initial population of the next subproblem. This method is applied to evolve agents to play keep-away soccer, a subproblem of robotic soccer that requires cooperation among multiple agents in a dynamic environment. The layered learning paradigm allows GP to evolve better solutions faster than standard GP. Results show that the layered learning GP outperforms standard GP by evolving a lower tness faster and an overall better tness. Results indicate a wide area of future research with layered learning in GP.

@mastersthesis{gustafson:mastersthesis, abstract = {We present an alternative to standard genetic programming (GP) that applies layered learning techniques to decompose a problem. GP is applied to subproblems sequentially, where the population in the last generation of a subproblem is used as the initial population of the next subproblem. This method is applied to evolve agents to play keep-away soccer, a subproblem of robotic soccer that requires cooperation among multiple agents in a dynamic environment. The layered learning paradigm allows GP to evolve better solutions faster than standard GP. Results show that the layered learning GP outperforms standard GP by evolving a lower tness faster and an overall better tness. Results indicate a wide area of future research with layered learning in GP.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Manhattan, KS, USA}, author = {Gustafson, Steven M.}, biburl = {https://www.bibsonomy.org/bibtex/2fef079343ef377299f6b75b265f6f80c/brazovayeye}, email = {smg@cs.nott.ac.uk}, interhash = {cb173dce45cd74a6a1a9f8dbdc381f9a}, intrahash = {fef079343ef377299f6b75b265f6f80c}, keywords = {algorithms, genetic programming}, month = {December}, notes = {Related Publications from Masters Thesis: William H. Hsu and Steven M. Gustafson. Wrappers for automatic parameter tuning in multi-agent optimization by genetic programming. In IJCAI-2001 Workshop on Wrappers for Performance Enhancement in Knowledge Discovery in Databases (KDD), Seattle, Washington, USA, 4 August 2001. \cite{hsu:2001:waptmaoGP} W. H. Hsu and S. M. Gustafson. Genetic Programming for Layered Learning of Multi-agent Tasks. In Late-Breaking Papers of the Genetic and Evolutionary Computation Conference (GECCO-2001), San Francisco, CA, June, 2001. \cite{hsu:2001:gpllmt} S. M. Gustafson and W. H. Hsu. Layered learning in genetic programming for a co-operative robot soccer problem. In J. F. Miller et al, editors, Proceedings of EuroGP'2001, v. 2038 of LNCS,p ages 291--301, Lake Como, Italy, 18-20 April 2001. Springer-Verlag. \cite{gustafson:2001:EuroGP}}, school = {Kansas State University}, timestamp = {2008-06-19T17:40:46.000+0200}, title = {Layered learning in genetic programming for a co-operative robot soccer problem}, url = {http://citeseer.ist.psu.edu/450396.html}, year = 2000 }