# Multi-Agent Dynamic Area Coverage Based on Reinforcement Learning with Connected Agents

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/multi-agent-dynamic-area-coverage-based-on-reinforcement-learning-with-connected/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Fatih Aydemir,Aydın Çetin |
| Citations | 16 |
| DOI | 10.32604/csse.2023.031116 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://file.techscience.com/ueditor/files/csse/TSP_CSSE-45-1/TSP_CSSE_31116/TSP_CSSE_31116.pdf |
| OpenAlex ID | https://openalex.org/W4292179081 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Fatih Aydemir](https://scholariq.org/researchers/fatih-aydemir/)

## Paper journal

- [Computer Systems Science and Engineering](https://scholariq.org/journals/computer-systems-science-and-engineering/)

## Paper primary topic

- [Distributed Control Multi-Agent Systems](https://scholariq.org/topics/distributed-control-multi-agent-systems/)

## Paper topics

- [Distributed Control Multi-Agent Systems](https://scholariq.org/topics/distributed-control-multi-agent-systems/)
- [UAV Applications and Optimization](https://scholariq.org/topics/uav-applications-and-optimization/)
- [Robotic Path Planning Algorithms](https://scholariq.org/topics/robotic-path-planning-algorithms/)

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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.