83 citations · 180 across the 12 of their papers we have counts for
4 papers · 1 filter
MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning
Sonia Baee, Erfan Pakdamanian, Inki Kim +3
Inspired by human visual attention, we propose a novel inverse reinforcement learning formulation using Maximum Entropy Deep Inverse Reinforcement Learning (MEDIRL) for predicting…
SaSTL: Spatial Aggregation Signal Temporal Logic for Runtime Monitoring in Smart Cities
Meiyi Ma, Ezio Bartocci, Eli Lifland +2
We present SaSTL -- a novel Spatial Aggregation Signal Temporal Logic -- for the efficient runtime monitoring of safety and performance requirements in smart cities. We first descr…
A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors
Josephine Lamp, Simone Silvetti, Marc Breton +2
Type I Diabetes (T1D) is a chronic disease in which the body's ability to synthesize insulin is destroyed. It can be difficult for patients to manage their T1D, as they must contro…
A Case Study of Trust on Autonomous Driving
Shili Sheng, Erfan Pakdamanian, Kyungtae Han +4
As autonomous vehicles have benefited the society, understanding the dynamic change of humans' trust during human-autonomous vehicle interaction can help to improve the safety and…