# Joint Trajectory and Offloading Optimization in Uav-Assisted Mec Via Federated Multi-Agent Reinforcement Learning and Potential Fields

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/joint-trajectory-and-offloading-optimization-in-uav-assisted-mec-via-federated/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Cong Wang,Peng Liu,Ying Yuan,Sancheng Peng,Guorui Li |
| Citations | 0 |
| DOI | 10.2139/ssrn.5376888 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | green |
| OA URL | https://doi.org/10.2139/ssrn.5376888 |
| OpenAlex ID | https://openalex.org/W4412859881 |
| Type | preprint |
| Year | 2025 |

## Paper authors

- [Ying Yuan](https://scholariq.org/researchers/ying-yuan/)

## Paper journal

- [SSRN Electronic Journal](https://scholariq.org/journals/ssrn-electronic-journal/)

## Paper primary topic

- [UAV Applications and Optimization](https://scholariq.org/topics/uav-applications-and-optimization/)

## Paper topics

- [UAV Applications and Optimization](https://scholariq.org/topics/uav-applications-and-optimization/)
- [Vehicular Ad Hoc Networks (VANETs)](https://scholariq.org/topics/vehicular-ad-hoc-networks-vanets/)
- [Distributed Control Multi-Agent Systems](https://scholariq.org/topics/distributed-control-multi-agent-systems/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.