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cs.LG2024
Continuous Mean-Zero Disagreement-Regularized Imitation Learning (CMZ-DRIL)
Noah Ford, Ryan W. Gardner, Austin Juhl +1
Machine-learning paradigms such as imitation learning and reinforcement learning can generate highly performant agents in a variety of complex environments. However, commonly used…
cs.LG2022★ 4 cited
A Risk-Sensitive Approach to Policy Optimization
Jared Markowitz, Ryan W. Gardner, Ashley Llorens +2
Standard deep reinforcement learning (DRL) aims to maximize expected reward, considering collected experiences equally in formulating a policy. This differs from human decision-mak…