# Cooperative Cognitive Dynamic System in UAV Swarms: Reconfigurable Mechanism and Framework

arXiv: https://arxiv.org/abs/2405.11281 · HTML: https://mlsanity.com/paper/2405.11281/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 20 references that are in the map.
- First posted on arXiv 18 May 2024.

## Builds on (most cited first, 1 of 1)

- [Unmanned Aerial Vehicle Swarm-Enabled Edge Computing: Potentials, Promising Technologies, and Challenges](https://mlsanity.com/paper/2201.08517/) (2022)

## Built on by (most cited first, 7 of 7)

- [Joint Computation Offloading and Resource Allocation for Uncertain Maritime MEC via Cooperation of UAVs and Vessels](https://mlsanity.com/paper/2506.15225/) (2025)
- [CNN+Transformer Based Anomaly Traffic Detection in UAV Networks for Emergency Rescue](https://mlsanity.com/paper/2503.20355/) (2025)
- [Generative AI-Enhanced Cooperative MEC of UAVs and Ground Stations for Unmanned Surface Vehicles](https://mlsanity.com/paper/2502.08119/) (2025)
- [Hierarchical Task Offloading for UAV-Assisted Vehicular Edge Computing via Deep Reinforcement Learning](https://mlsanity.com/paper/2507.05722/) (2025)
- [Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning](https://mlsanity.com/paper/2508.00938/) (2025)
- [Hierarchical Task Offloading and Trajectory Optimization in Low-Altitude Intelligent Networks Via Auction and Diffusion-based MARL](https://mlsanity.com/paper/2512.11862/) (2025)
- [Prompt-Driven Low-Altitude Edge Intelligence: Modular Agents and Generative Reasoning](https://mlsanity.com/paper/2602.14003/) (2026)

## Abstract (arXiv)

As the demands for immediate and effective responses increase in both civilian and military domains, the unmanned aerial vehicle (UAV) swarms emerge as effective solutions, in which multiple cooperative UAVs can work together to achieve specific goals. However, how to manage such complex systems to ensure real-time adaptability lack sufficient researches. Hence, in this paper, we propose the cooperative cognitive dynamic system (CCDS), to optimize the management for UAV swarms. CCDS leverages a hierarchical and cooperative control structure that enables real-time data processing and decision. Accordingly, CCDS optimizes the UAV swarm management via dynamic reconfigurability and adaptive intelligent optimization. In addition, CCDS can be integrated with the biomimetic mechanism to efficiently allocate tasks for UAV swarms. Further, the distributed coordination of CCDS ensures reliable and resilient control, thus enhancing the adaptability and robustness. Finally, the potential challenges and future directions are analyzed, to provide insights into managing UAV swarms in dynamic heterogeneous networking.