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Dynamic Selection of Neural Network Modules based on Cellular Automata for Complex Behaviors  

Kim, Kyung-Joong (연세대학교 컴퓨터과학과)
Cho, Sung-Bae (연세대학교 컴퓨터과학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.51, no.4, 2002 , pp. 160-166 More about this Journal
Abstract
Since conventional mobile robot control with one module has limitation to solve complex problems, there have been a variety of works on combining multiple modules for solving them. Recently, many researchers attempt to develop mobile robot controllers using artificial life techniques. In this paper, we develop a mobile robot controller using cellular automata based neural networks, where complex tasks are divided to simple sub-tasks and optimal neural structure of each sub-task is explored by genetic algorithm. Neural network modules are combined dynamically using the action selection mechanism, where basic behavior modules compete each other by inhibition and cooperation. Khepera mobile robot simulator is used to verify the proposed model. Experimental results show that complex behaviors emerge from the combination of low-level behavior modules.
Keywords
Cellular Automata;
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