5 citations · 14 across the 10 of their papers we have counts for
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cs.RO2017
Inverse Reinforcement Learning Under Noisy Observations
Shervin Shahryari, Prashant Doshi
We consider the problem of performing inverse reinforcement learning when the trajectory of the expert is not perfectly observed by the learner. Instead, a noisy continuous-time ob…
cs.AI2017★ 5 cited
Actor-Critic for Linearly-Solvable Continuous MDP with Partially Known Dynamics
Tomoki Nishi, Prashant Doshi, Michael R. James +1
In many robotic applications, some aspects of the system dynamics can be modeled accurately while others are difficult to obtain or model. We present a novel reinforcement learning…