no code implementations • 26 Nov 2018 • Hisao Katsumi, Takuya Hiraoka, Koichiro Yoshino, Kazeto Yamamoto, Shota Motoura, Kunihiko Sadamasa, Satoshi Nakamura
It is required that these systems have sufficient supporting information to argue their claims rationally; however, the systems often do not have enough of such information in realistic situations.
no code implementations • 28 Jun 2018 • Kazeto Yamamoto, Takashi Onishi, Yoshimasa Tsuruoka
One potential solution to this problem is to combine reinforcement learning with automated symbol planning and utilize prior knowledge on the domain.
Hierarchical Reinforcement Learning reinforcement-learning +1
no code implementations • 19 Jun 2018 • Shota Motoura, Kazeto Yamamoto, Shumpei Kubosawa, Takashi Onishi
This paper proposes a method to translate multilevel flow modeling (MFM) into a first-order language (FOL), which enables the utilisation of logical techniques, such as inference engines and abductive reasoners.