システム制御情報学会論文誌
Online ISSN : 2185-811X
Print ISSN : 1342-5668
ISSN-L : 1342-5668
論文
深層強化学習とDeep Neuroevolution によるロボティックスワームの群れ行動生成と解析
森本 大智平賀 元彰大倉 和博松村 嘉之
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ジャーナル オープンアクセス

2020 年 33 巻 5 号 p. 163-170

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This study proposes a method to apply deep neural networks to controllers of robotic swarms. In a typical approach to design controllers, the designer has to define the features extracted from sensory inputs in advance. By applying deep neural networks with convolution layers, it can automatically extract features from sensory inputs. We applied two methods to train the deep neural networks, i.e.,deep reinforcement learning and deep neuroevolution. The controllers were tested in a path-formation task using computer simulations. Compared with deep reinforcement learning, deep neuroevolution was able to generate collective behavior even in sparse reward settings.

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