Situated GAIL: Multitask imitation using task-conditioned adversarial inverse reinforcement learning

no code implementations • 1 Nov 2019 • Kyoichiro Kobayashi, Takato Horii, Ryo Iwaki, Yukie Nagai, Minoru Asada

This study proposes an extended framework called situated GAIL (S-GAIL), in which a task variable is introduced to both the discriminator and generator of the GAIL framework.

Imitation Learning reinforcement-learning +1

On- and Off-Policy Monotonic Policy Improvement

no code implementations • 10 Oct 2017 • Ryo Iwaki, Minoru Asada

Monotonic policy improvement and off-policy learning are two main desirable properties for reinforcement learning algorithms.

reinforcement-learning Reinforcement Learning (RL)