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Notes on cyber-physical systems
4 notes
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
The paper presents an online anomaly detection framework for connected vehicles that uses a deep Q-network with self-attention to select suitable detectors, an ensemble of statistical drift detectors to monitor input…
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
The paper proposes an online anomaly detection framework for autonomous cyber-physical systems (CPS), specifically connected vehicles, that combines three coordinated mechanisms: a deep Q-network with self-attention to…
Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy
Researchers have developed a new framework called OmniAct for building embodied agents that can operate in unstructured environments. This framework aims to address the challenges of managing both cyber and physical…
Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy
The researchers present a framework called OmniAct that aims to build persistent embodied agents for operation in unstructured environments. The framework integrates a multimodal semantic planner, an adaptive…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
