no code implementations • 5 Sep 2023 • Haozhe Lei, Quanyan Zhu
In the area of learning-driven artificial intelligence advancement, the integration of machine learning (ML) into self-driving (SD) technology stands as an impressive engineering feat.
1 code implementation • 11 Jun 2023 • Mingsheng Yin, Tao Li, Haozhe Lei, Yaqi Hu, Sundeep Rangan, Quanyan Zhu
To equip the navigation agent with sample-efficient learning and {zero-shot} generalization, this work proposes a novel physics-informed RL (PIRL) where a distance-to-target-based cost (standard in e2e) is augmented with physics-informed reward shaping.
no code implementations • 17 Dec 2022 • Haozhe Lei, Quanyan Zhu
To ensure traffic safety in self-driving environments and respond to vehicle-human interaction challenges such as jaywalking, we propose Level-$k$ Meta Reinforcement Learning (LK-MRL) algorithm.
1 code implementation • 29 Jul 2022 • Tao Li, Haozhe Lei, Quanyan Zhu
It leads to two online attack schemes: Intermittent Attack and Persistent Attack, which enable the attacker to learn an optimal sampling attack, defined by an $\epsilon$-first-order stationary point, within $\mathcal{O}(\epsilon^{-2})$ iterations.