14 citations · 14 across the 1 of their papers we have counts for
4 papers · 1 filter
Machine versus Human Attention in Deep Reinforcement Learning Tasks
Sihang Guo, Ruohan Zhang, Bo Liu +4
Deep reinforcement learning (RL) algorithms are powerful tools for solving visuomotor decision tasks. However, the trained models are often difficult to interpret, because they are…
Efficiently Guiding Imitation Learning Agents with Human Gaze
Akanksha Saran, Ruohan Zhang, Elaine Schaertl Short +1
Human gaze is known to be an intention-revealing signal in human demonstrations of tasks. In this work, we use gaze cues from human demonstrators to enhance the performance of agen…
Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset
Ruohan Zhang, Calen Walshe, Zhuode Liu +6
Large-scale public datasets have been shown to benefit research in multiple areas of modern artificial intelligence. For decision-making research that requires human data, high-qua…
An initial attempt of combining visual selective attention with deep reinforcement learning
Liu Yuezhang, Ruohan Zhang, Dana H. Ballard
Visual attention serves as a means of feature selection mechanism in the perceptual system. Motivated by Broadbent's leaky filter model of selective attention, we evaluate how such…