• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.289-293
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• 2002

Learning Classifier System (LCS) finds a new rule set using genetic algorithm (GA). In this paper, The Zeroth Level Classifier System (ZCS) is applied to evolving the strategy of a robot soccer simulation game (SimuroSot), which is a state varying dynamical system changed over time, as GBML (Genetic Based Machine Learning) and we show the effectiveness of the proposed scheme through the simulation of robot soccer.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.96-102
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• 2006

In this study, an optimization routine with genetic algorithms is coupled for the selection of free variables for the production of a control signal for the motion of wave board in the numerical wave tank. An excitation function for the controlling of the wave board is formulated on basis of amplitude modulation for the generation of nonlinear wave packets. The found variables by the optimization serve for the determination of wave board motion both with the computation and with the experiment. The breaking criterion of the water waves is implemented as boundary condition for the optimization procedure. With the analysis of the time registration on the local position in the wave tank the optimization routine is accomplished until the given design wave with defined surface elevation is found. Water surface elevation and associated fields of velocity and pressure are numerically computed.