arXiv:2608.21444v1 Announce Type: new
Abstract: Multi-drone systems are increasingly positioned for safety-critical missions such as search and rescue (SAR) and critical infrastructure monitoring. Ye...
By Timothy Merritt, Alejandro Jarabo-Pe\~nas, Juan Bravo-Arrabal, Maria-Theresa Bahodi, Anders Lyhne Christensen
The article explores neuro-symbolic agentic AI (NSAAI) as a framework for enhancing the reliability and adaptability of networked low‑altitude UAVs. It outlines NSAAI’s strengths in data efficiency, compositional generalization, continual learning, and zero‑shot transfer, and presents a reference architecture that integrates task management, neuro‑symbolic planning, verification, metacognition, skill execution, and network interaction. A case study of an urban fire‑inspection mission demonstrates how a UAV can coordinate sensing, cloud access, and verified image‑delivery skills under intermittent connectivity, illustrating NSAAI’s potential for reusable skills, evidence‑grounded decision‑making, and adaptive mission execution.
The paper explores offline large language models as decision‑support tools for air operations, where analysts must work with doctrine and imagery under limited connectivity. It presents a modular retrieval‑augmented architecture that handles both text and image inputs from technical manuals and can operate without Internet access. A pilot study with four Brazilian Air Force image analysts shows the system matches human performance on doctrinal knowledge tests while completing the task in a fraction of the time, and it highlights the high cognitive load of manual target reporting.
By Joao P. A. Dantas, Jelton A. Cunha, Gabriel Dietzsch
The paper proposes Neuro‑Symbolic Agentic AI (NSAAI) as a framework that blends neural grounding, symbolic reasoning, and closed‑loop interaction to enhance decision‑making for networked low‑altitude UAVs. It outlines NSAAI’s strengths in data efficiency, compositional generalization, continual learning, and zero‑shot transfer, and presents a reference architecture covering task management, planning, verification, skill execution, and network interaction. An urban fire‑inspection simulation demonstrates how a UAV can coordinate sensing, cloud access, and verified image‑delivery skills under intermittent connectivity, illustrating NSAAI’s potential for reusable skills, evidence‑grounded decisions, and adaptive mission execution.
By Yuqi Ping, Tianhao Liang, Nanchi Su, Guangyu Lei, Junwei Wu, Qinyu Zhang, Tingting Zhang
arXiv:2607. 23438v1 Announce Type: new Abstract: As AI systems increasingly exhibit agentic behavior, discussions of autonomy often conflate what systems are technically capable of doing with what they should be permitted to do in practice.
By Haining Zheng, Qian Dong, Rodolfo K. Depena, Jonathan D. Bhatia, Feng Xiao, Peng Xu
arXiv:2503.13415v2 Announce Type: replace-cross
Abstract: With the rapid development of artificial intelligence, intelligent decision-making techniques have gradually surpassed human levels in variou...
By Weiqiang Jin, Hongyang Du, Shixiang Tang, Biao Zhao, Guang Yang