Constrained Deep Q-Learning Gradually Approaching Ordinary Q-Learning. - Shota Ohnishi; Eiji Uchibe; Yotaro Yamaguchi; Kosuke Nakanishi; Yuji Yasui; Shin Ishii (Frontiers Neurorobotics, 2019)

Deep Adversarial Reinforcement Learning With Noise Compensation by Autoencoder. - Kohei Ohashi; Kosuke Nakanishi; Wataru Sasaki; Yuji Yasui; Shin Ishii (IEEE Access, 2021)

Deep Adversarial Reinforcement Learning Method to Generate Control Policies Robust Against Worst-Case Value Predictions. - Kohei Ohashi; Kosuke Nakanishi; Yuji Yasui; Shin Ishii (IEEE Access, 2023)

Orthogonal Adversarial Deep Reinforcement Learning for Discrete- and Continuous-Action Problems. - Kohei Ohashi; Kosuke Nakanishi; Nao Goto; Yuji Yasui; Shin Ishii (IEEE Access, 2024)

Robust off-policy Reinforcement Learning via Soft Constrained Adversary. - Kosuke Nakanishi; Akihiro Kubo; Yuji Yasui; Shin Ishii (CoRR, 2024)

Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation. - Kosuke Nakanishi; Akihiro Kubo; Yuji Yasui; Shin Ishii (CoRR, 2025)