Shotaro Kamio

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We propose an integrated technique of genetic programming (GP) and reinforcement learning (RL) that allows a real robot to execute real-time learning. Our technique does not need a precise simulator because learning is done with a real robot. Moreover, our technique makes it possible to learn optimal actions in real robots. We show the result of an(More)
We introduce a technique that allows a real robot to execute real-time learning, in which GP and RL are integrated. In our former research, we showed the result of an experiment with a real robot " AIBO " and proved the technique performed better than the traditional Q-learning method. Based on the proposed technique , we can acquire the common programs(More)
We have been studying the techniques for evolutionary robotics and experimenting with various robots applied evolutionary methods. We have paid special attentions to real robots and multi-agent problems with them. In this research domain, we named them as " Ingeniously Behaving Agents (IBA) ". This paper shows several techniques developed in our IBA(More)
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