2 citations · 3 across the 4 of their papers we have counts for
4 papers
Inverse Contextual Bandits without Rewards: Learning from a Non-Stationary Learner via Suffix Imitation
Yuqi Kong, Xiao Zhang, Weiran Shen
We study the Inverse Contextual Bandit (ICB) problem, in which a learner seeks to optimize a policy while an observer, who cannot access the learner's rewards and only observes act…
Learning Diverse Policies with Soft Self-Generated Guidance
Guojian Wang, Faguo Wu, Xiao Zhang +1
Reinforcement learning (RL) with sparse and deceptive rewards is challenging because non-zero rewards are rarely obtained. Hence, the gradient calculated by the agent can be stocha…
Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery
Xiao Zhang, Hai Zhang, Hongtu Zhou +4
Safety is one of the main challenges in applying reinforcement learning to realistic environmental tasks. To ensure safety during and after training process, existing methods tend…
Augmented Q Imitation Learning (AQIL)
Xiao Lei Zhang, Anish Agarwal
The study of unsupervised learning can be generally divided into two categories: imitation learning and reinforcement learning. In imitation learning the machine learns by mimickin…