Genetic Programming for Classifying Cancer Data and Controlling Humanoid Robots

Abstract

In this chapter, we show the real-world applicationsof genetic programming (GP) to bioinformatics androbotics. In the bioinformatics application, we proposemajority voting technique for the prediction of theclass of a test sample. In the application to robotics,we use GP to generate the motion sequences of humanoidrobots. We introduce an integrated approach, i.e., thecombination of GP and reinforcement learning, to designthe desirable motions. The effectiveness of ourproposed approaches is demonstrated by performingexperiments with real data, i.e., classifying realmicro-array gene expression profiles and controllingreal humanoid robots.