Assistant Professor Yunduan Cui et al. received the best paper award at the 28th Annual Conference of the Japanese Neural Network Society (JNNS2018) which was held from October 24th to 27th at Okinawa Institute of Science and Technology (OIST) for their work published in Neural Networks:
Yunduan Cui, Takamitsu Matsubara, Kenji Sugimoto
“Kernel dynamic policy programming: Applicable reinforcement learning to robot systems with high dimensional states”,
Neural Networks 94 (2017): pp. 13-23.