%0 Conference Paper %1 bajurnow:2004:llfegsbisp %A Bajurnow, Andrei %A Ciesielski, Vic %B Proceedings of the 2004 IEEE Congress on Evolutionary Computation %C Portland, Oregon %D 2004 %I IEEE Press %K Computation Evolutionary Games agents, algorithms, and genetic intelligent programming, %P 1828--1835 %T Layered Learning for Evolving Goal Scoring Behavior in Soccer Players %U http://goanna.cs.rmit.edu.au/~vc/papers/cec2004-bajurnow.pdf %X Layered learning allows decomposition of the stages of learning in a problem domain. We apply this technique to the evolution of goal scoring behavior in soccer players and show that layered learning is able to find solutions comparable to standard genetic programs more reliably. The solutions evolved with layers have a higher accuracy but do not make as many goal attempts. We compared three variations of layered learning and find that maintaining the population between layers as the encapsulated learnt layer is introduced to be the most computationally efficient. The quality of solutions found by layered learning did not exceed those of standard genetic programming in terms of goal scoring ability. %@ 0-7803-8515-2

@inproceedings{bajurnow:2004:llfegsbisp, abstract = {Layered learning allows decomposition of the stages of learning in a problem domain. We apply this technique to the evolution of goal scoring behavior in soccer players and show that layered learning is able to find solutions comparable to standard genetic programs more reliably. The solutions evolved with layers have a higher accuracy but do not make as many goal attempts. We compared three variations of layered learning and find that maintaining the population between layers as the encapsulated learnt layer is introduced to be the most computationally efficient. The quality of solutions found by layered learning did not exceed those of standard genetic programming in terms of goal scoring ability.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Portland, Oregon}, author = {Bajurnow, Andrei and Ciesielski, Vic}, biburl = {https://www.bibsonomy.org/bibtex/2b8939a7d8d2dc657d4f5fce0e1d22fe9/brazovayeye}, booktitle = {Proceedings of the 2004 IEEE Congress on Evolutionary Computation}, interhash = {cd2e0ddac9ca3e09fa68c09bd1538e57}, intrahash = {b8939a7d8d2dc657d4f5fce0e1d22fe9}, isbn = {0-7803-8515-2}, keywords = {Computation Evolutionary Games agents, algorithms, and genetic intelligent programming,}, month = {20-23 June}, notes = {CEC 2004 - A joint meeting of the IEEE, the EPS, and the IEE.}, pages = {1828--1835}, publisher = {IEEE Press}, size = {8 pages}, timestamp = {2008-06-19T17:36:08.000+0200}, title = {Layered Learning for Evolving Goal Scoring Behavior in Soccer Players}, url = {http://goanna.cs.rmit.edu.au/~vc/papers/cec2004-bajurnow.pdf}, year = 2004 }