%0 Book Section %1 Paul:2006:GPTP %A Paul, Topon Kumar %A Iba, Hitoshi %B Genetic Programming Theory and Practice IV %C Ann Arbor %D 2006 %E Riolo, Rick L. %E Soule, Terence %E Worzel, Bill %I Springer %K Q-learning algorithms, breast cancer, carcinoma, classification, cooperation cooperative dance, frequently genes, genetic humanoid lung majority movers' occurring piano problem, programming, robots, transportation, voting, %P - %T Genetic programming for classifying cancer data and controlling humanoid robots %V 5 %X we show the real-world applications of genetic programming (GP) to bioinformatics and robotics. In the bioinformatics application, we propose majority voting technique for the prediction of the class of a test sample. In the application to robotics, we use GP to generate the motion sequences of humanoid robots. We introduce an integrated approach, i.e., the combination of GP and reinforcement learning, to design the desirable motions. The effectiveness of our proposed approaches is demonstrated by performing experiments with real data, i.e., classifying real micro-array gene expression profiles and controlling real humanoid robots. %& 10 %@ 0-387-33375-4

@incollection{Paul:2006:GPTP, abstract = {we show the real-world applications of genetic programming (GP) to bioinformatics and robotics. In the bioinformatics application, we propose majority voting technique for the prediction of the class of a test sample. In the application to robotics, we use GP to generate the motion sequences of humanoid robots. We introduce an integrated approach, i.e., the combination of GP and reinforcement learning, to design the desirable motions. The effectiveness of our proposed approaches is demonstrated by performing experiments with real data, i.e., classifying real micro-array gene expression profiles and controlling real humanoid robots.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Ann Arbor}, author = {Paul, Topon Kumar and Iba, Hitoshi}, biburl = {https://www.bibsonomy.org/bibtex/20d6914e8a7511976ad86ef5de0db46c7/brazovayeye}, booktitle = {Genetic Programming Theory and Practice {IV}}, chapter = 10, editor = {Riolo, Rick L. and Soule, Terence and Worzel, Bill}, interhash = {e47c3d9616258933349272d577a9a7ba}, intrahash = {0d6914e8a7511976ad86ef5de0db46c7}, isbn = {0-387-33375-4}, keywords = {Q-learning algorithms, breast cancer, carcinoma, classification, cooperation cooperative dance, frequently genes, genetic humanoid lung majority movers' occurring piano problem, programming, robots, transportation, voting,}, month = {11-13 May}, notes = {part of \cite{Riolo:2006:GPTP} Published Jan 2007 after the workshop. Majority voting MVGPC NEJM_Supplement 203 lung tumour, five-class. Box moving, interactive evolution, humanoid robot. HOAP-1, Q-learning 238 states. cooperative transportation. dance (3 HOAP-1 robots).}, pages = {-}, publisher = {Springer}, series = {Genetic and Evolutionary Computation}, size = {18 pages}, timestamp = {2008-06-19T17:49:19.000+0200}, title = {Genetic programming for classifying cancer data and controlling humanoid robots}, volume = 5, year = 2006 }