JSAI2018

Presentation information

Oral presentation

General Session » [General Session] 2. Machine Learning

[1N1] [General Session] 2. Machine Learning

Tue. Jun 5, 2018 1:20 PM - 3:00 PM Room N (2F Sakurajima)

座長:原 聡(大阪大学)

2:40 PM - 3:00 PM

[1N1-05] Social reinforcement learning with shared reference satisficing

〇Noriaki Sonota1, Takumi Kamiya2, Yu Kono3, Tatsuji Takahashi1 (1. School of Science and Engineering, Tokyo Denki University, 2. Graduate School of Tokyo Denki Univerity, 3. DeNA Co., Ltd.)

Keywords:social learning, bounded rationality, imitation

animals learn not only through individual trial-and-error, but also from other individuals. It is known that vertebrates cleverly utilize learning strategies such as copy-when-uncertain and copy-successful-individuals. These strategies can be applied to social reinforcement learning, although their formalizations are yet to be established. We propose a social reinforcement learning algorithm with a very narrow information sharing. The algorithm exploits RS value function that models the satisficing principle for exploration and exploitation.