7 citations · 7 across the 4 of their papers we have counts for
4 papers
Distorted Distributional Policy Evaluation for Offline Reinforcement Learning
Ryo Iwaki, Takayuki Osogami
While Distributional Reinforcement Learning (DRL) methods have demonstrated strong performance in online settings, its success in offline scenarios remains limited. We hypothesize…
Mirror Descent Actor Critic via Bounded Advantage Learning
Ryo Iwaki
Regularization is a core component of recent Reinforcement Learning (RL) algorithms. Mirror Descent Value Iteration (MDVI) uses both Kullback-Leibler divergence and entropy as regu…
Situated GAIL: Multitask imitation using task-conditioned adversarial inverse reinforcement learning
Kyoichiro Kobayashi, Takato Horii, Ryo Iwaki +2
Generative adversarial imitation learning (GAIL) has attracted increasing attention in the field of robot learning. It enables robots to learn a policy to achieve a task demonstrat…
On- and Off-Policy Monotonic Policy Improvement
Ryo Iwaki, Minoru Asada
Monotonic policy improvement and off-policy learning are two main desirable properties for reinforcement learning algorithms. In this paper, by lower bounding the performance diffe…