5 citations · 14 across the 10 of their papers we have counts for
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cs.LG2018
A Survey of Inverse Reinforcement Learning: Challenges, Methods and Progress
Saurabh Arora, Prashant Doshi
Inverse reinforcement learning (IRL) is the problem of inferring the reward function of an agent, given its policy or observed behavior. Analogous to RL, IRL is perceived both as a…
cs.LG2018
Reinforcement Learning for Heterogeneous Teams with PALO Bounds
Roi Ceren, Prashant Doshi, Keyang He
We introduce reinforcement learning for heterogeneous teams in which rewards for an agent are additively factored into local costs, stimuli unique to each agent, and global rewards…
cs.LG2018
A Framework and Method for Online Inverse Reinforcement Learning
Saurabh Arora, Prashant Doshi, Bikramjit Banerjee
Inverse reinforcement learning (IRL) is the problem of learning the preferences of an agent from the observations of its behavior on a task. While this problem has been well invest…