SUNA によるシミュレーション上での二足歩行動作学習

井上 湧太, ヴァルガス ダニロ

研究成果: Contribution to journalArticle

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<p>SUNA is currently one of the most adaptive neuroevolution methods which is able to tackle different problems efficiently. However, many questions remain unanswered. In this research, we applied SUNA to the bipedal-walking problem and evaluate it general learning properties. The results show that even without any modificiations SUNA is able to learn in this environment. Moreover, contrary to many other methods, it is continuously improving its average rewards showing a near open-ended learning.</p>
寄稿の翻訳されたタイトルLearning to Bipedal Walking on Simulation with SUNA
元の言語Japanese
ページ(範囲)1Z202-1Z202
ジャーナル人工知能学会全国大会論文集
2018
発行部数0
DOI
出版物ステータス出版済み - 2018
外部発表Yes

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