ロボティクス・メカトロニクス講演会講演概要集
Online ISSN : 2424-3124
セッションID: 2A1-M08
会議情報
2A1-M08 高速学習型ネットワーク構造をもつニューラルモデルの開発(進化・学習とロボティクス)
渡辺 美知子古川 正志
著者情報
会議録・要旨集 フリー

詳細
抄録
Being inspired by the existence of the small world networks in the neural net, we designed new structures of an artificial neural network and compare them with ones of conventional neural networks from a viewpoint of learning. We adopt the evolutionary computation for assigning proper weights to synapses. A learning test problem is given that a small robot located at the corner in a square field reaches the light source as fast as it can drive. Results in simulation shows that a small robot with a structure of small world networks in the nerves system can reach the light source faster than any other structures.
著者関連情報
© 2007 一般社団法人 日本機械学会
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