- author = "Topon Kumar Paul and Hitoshi Iba",
- title = "Genetic programming for classifying cancer data and controlling humanoid robots",
- booktitle = "Genetic Programming Theory and Practice {IV}",
- year = "2006",
- editor = "Rick L. Riolo and Terence Soule and Bill Worzel",
- volume = "5",
- series = "Genetic and Evolutionary Computation",
- pages = "41--59",
- address = "Ann Arbor",
- month = "11-13 " # may,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, breast cancer, classification, cooperation dance, cooperative transportation, frequently occurring genes, humanoid robots, lung carcinoma, majority voting, piano movers' problem, Q-learning",
- ISBN = "0-387-33375-4",
-
DOI = "
doi:10.1007/978-0-387-49650-4_4",
- size = "18 pages",
- abstract = "In this chapter, 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.",
-
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).",
