# FLDQN: Cooperative Multi-Agent Federated Reinforcement Learning for Solving Travel Time Minimization Problems in Dynamic Environments Using SUMO Simulation

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/fldqn-cooperative-multi-agent-federated-reinforcement-learning-for-solving/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Abdul Wahab Mamond,Majid Kundroo,Seong-eun Yoo,Seonghoon Kim,Taehong Kim |
| Citations | 23 |
| DOI | 10.3390/s25030911 |
| Fields | Engineering,Social Sciences |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/1424-8220/25/3/911/pdf?version=1738639669 |
| OpenAlex ID | https://openalex.org/W4407143222 |
| PMID | 39943549 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Majid Kundroo](https://scholariq.org/researchers/majid-kundroo/)

## Paper journal

- [Sensors](https://scholariq.org/journals/sensors/)

## Paper primary topic

- [Traffic control and management](https://scholariq.org/topics/traffic-control-and-management/)

## Paper topics

- [Traffic control and management](https://scholariq.org/topics/traffic-control-and-management/)
- [Transportation Planning and Optimization](https://scholariq.org/topics/transportation-planning-and-optimization/)
- [Transportation and Mobility Innovations](https://scholariq.org/topics/transportation-and-mobility-innovations/)

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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.