6 papers
Manifold-Constrained Energy-Based Transition Models for Offline Reinforcement Learning
Zeyu Fang, Zuyuan Zhang, Mahdi Imani +1
Model-based offline reinforcement learning is brittle under distribution shift: policy improvement drives rollouts into state--action regions weakly supported by the dataset, where…
Geometry of Drifting MDPs with Path-Integral Stability Certificates
Zuyuan Zhang, Mahdi Imani, Tian Lan
Real-world reinforcement learning is often \emph{nonstationary}: rewards and dynamics drift, accelerate, oscillate, and trigger abrupt switches in the optimal action. Existing theo…
ACDZero: MCTS Agent for Mastering Automated Cyber Defense
Yu Li, Sizhe Tang, Rongqian Chen +5
Automated cyber defense (ACD) seeks to protect computer networks with minimal or no human intervention, reacting to intrusions by taking corrective actions such as isolating hosts,…
Global Optimization on Graph-Structured Data via Gaussian Processes with Spectral Representations
Shu Hong, Yongsheng Mei, Mahdi Imani +1
Bayesian optimization (BO) is a powerful framework for optimizing expensive black-box objectives, yet extending it to graph-structured domains remains challenging due to the discre…
Perception Graph for Cognitive Attack Reasoning in Augmented Reality
Rongqian Chen, Shu Hong, Rifatul Islam +3
Augmented reality (AR) systems are increasingly deployed in tactical environments, but their reliance on seamless human-computer interaction makes them vulnerable to cognitive atta…
A Neurosymbolic Framework for Interpretable Cognitive Attack Detection in Augmented Reality
Rongqian Chen, Allison Andreyev, Yanming Xiu +7
Augmented Reality (AR) enriches human perception by overlaying virtual elements onto the physical world. However, this tight coupling between virtual and real content makes AR vuln…