arXiv AI

An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computing

arXiv:2605. 13221v2 Announce Type: replace Abstract: In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC).

arXiv AI

Jul 1

Locker-based Truck-Drone Routing with Integrated Considerations of Pickups, Deliveries, and No-Fly Zones

arXiv:2606. 30680v1 Announce Type: cross Abstract: Truck-drone delivery is an emerging last-mile logistics mode combining the long-haul capacity of trucks with the flexible service capability of drones.

By Xuanyu Liu, Hui Hu, Jiao Zhao, Ziliang Wang, Zhengbing He

reinforcement-learning robotics

arXiv AI

Jun 19

Oranits: Mission Assignment and Task Offloading in Open RAN-based ITS using Metaheuristic and Deep Reinforcement Learning

arXiv:2507. 19712v3 Announce Type: replace-cross Abstract: In this paper, we explore mission assignment and task offloading in an Open Radio Access Network (Open RAN)-based intelligent transportation system (ITS), where autonomous vehicles leverage mobile edge computing for efficient processing.

By Ngoc Hung Nguyen, Nguyen Van Thieu, Quang-Trung Luu, Anh Tuan Nguyen, Senura Wanasekara, Nguyen Cong Luong, Fatemeh Kavehmadavani, Van-Dinh Nguyen

agents reinforcement-learning

arXiv AI

Jun 9

Efficient Onboard Vision-Language Inference in UAV-Enabled Low-Altitude Economy Networks via LLM-Enhanced Optimization

arXiv:2510. 10028v2 Announce Type: replace-cross Abstract: The rapid advancement of Low-Altitude Economy Networks (LAENets) has enabled a variety of applications, including aerial surveillance, environmental sensing, and semantic data collection.

By Yang Li, Ruichen Zhang, Yinqiu Liu, Guangyuan Liu, Abbas Jamalipour, Xianbin Wang, Dong In Kim

llms nlp reinforcement-learning multimodal

arXiv Machine Learning

Aug 11

ML-Based Hierarchical Prediction for Practical Energy Scheduling in Dynamic NTN-WPT Systems

arXiv:2608. 08804v1 Announce Type: cross Abstract: With advancements in long-distance wireless power transfer (WPT) and space-based energy technologies, integrating WPT into non-terrestrial networks (NTNs), referred to as NTN-WPT, is emerging as a promising approach for next-generation wireless networks.

By Zhanyu Ju, Wenchi Cheng

agents reinforcement-learning

arXiv Machine Learning

Aug 4

MA-HEAD-Net: Adaptive Rule-Guided Multi-Agent DRL for AoI Minimization in UAV-Assisted Emergency Networks

arXiv:2608. 01128v1 Announce Type: cross Abstract: In post-disaster scenarios, unmanned aerial vehicles (UAVs) are critical for establishing emergency communication networks.

By Yixin Zhang, Zhuohui Yao, Wenchi Cheng, Walid Saad

agents reinforcement-learning

arXiv Machine Learning

Jul 22

Multi-Timescale Latent-Action DRL for Joint Optimization in Edge-Cloud Networks

arXiv:2607. 18288v1 Announce Type: new Abstract: Load imbalance across edge and cloud layers degrades latency performance in hierarchical edge-cloud computing (HECC) systems under dynamic task arrivals and heterogeneous resources, leading to severe queuing delays and inefficient resource utilization.

By Vo Phi Son, Van-Dinh Nguyen, Ngoc Hung Nguyen, Trinh Van Chien, Symeon Chatzinotas

reinforcement-learning

Hugging Face Trending Papers

Jul 21

Reinforcement Learning for Delivery Drone-Based Participatory Sensing in Dynamic Environments

Using Unmanned Aerial Vehicle (UAV) for urban sensing has emerged as a powerful paradigm to monitor the status of the city, e. g.

rag reinforcement-learning robotics

arXiv Machine Learning

Jul 22

Reinforcement Learning for Delivery Drone-Based Participatory Sensing in Dynamic Environments

arXiv:2607. 18874v1 Announce Type: new Abstract: Using Unmanned Aerial Vehicle (UAV) for urban sensing has emerged as a powerful paradigm to monitor the status of the city, e.

By Xin Ouyang, Songxin Lei, Xusen Guo, Yutian Jiang, Sijie Ruan, Yuxuan Liang

rag reinforcement-learning robotics

arXiv Machine Learning

Jul 8

Joint Energy Management and Coordinated AIGC Workload Scheduling for Distributed Data Centers: A Diffusion-Aided Reward Shaping Approach

arXiv:2605. 02965v2 Announce Type: replace Abstract: Artificial intelligence-generated content (AIGC) has emerged as a transformative paradigm for automating the creation of diverse and customized content, giving rise to rapidly growing computational workloads in cloud data centers.

By Yang Fu, Peng Qin, Liming Chen, Zihao Zhang, Hao Yu, Yifei Wang

diffusion reinforcement-learning efficiency benchmarks

arXiv Machine Learning

Jun 17

OmniPlan: An Adaptive Framework for Timely and Near-Optimal Network Planning Optimization

arXiv:2606. 18105v1 Announce Type: cross Abstract: Network planning optimization is a fundamental problem across diverse domains, including transportation systems, communication networks, and power grids.

By Longlong Zhu, Jiashuo Yu, Zedi Chen, Yuhan Wu, Zhifan Jiang, Yuchen Xian, Yimeng Liu, Jiajie Su, Shaopeng Zhou, Xingyuan Li, Hongyan Liu, Xuan Liu, Dong Zhang, Chunming Wu, Xiang Chen

llms reinforcement-learning

arXiv Machine Learning

Jun 16

Diffusion Offline Reinforcement Learning for Fair and Energy-Efficient UAV-Assisted Wireless Networks

arXiv:2606. 16331v1 Announce Type: new Abstract: The integration of generative artificial intelligence with wireless communication and signal processing systems has opened new avenues for intelligent, data-driven decision-making in future 6G networks.

By Eslam Eldeeb, Hirley Alves

diffusion reinforcement-learning efficiency safety

arXiv AI

Aug 7

Multi-Agent Transformer for Queue-Level XR Traffic Scheduling in TSN Networks

arXiv:2608. 05340v1 Announce Type: cross Abstract: Time-Sensitive Networking (TSN) and Mobile Edge Computing (MEC) hold strong potential for enabling ultra-reliable low-latency communication for time-sensitive applications, such as eXtended Reality (XR).

By Marcos Carvalho, Fatih Temiz, Shavbo Salehi, Melike Erol-Kantarci, Daniel F. Macedo

llms agents reinforcement-learning

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