# Cooperative Multi-Type Multi-Agent Deep Reinforcement Learning for Resource Management in Space-Air-Ground Integrated Networks

arXiv: https://arxiv.org/abs/2308.03995 · HTML: https://mlsanity.com/paper/2308.03995/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 28 references that are in the map.
- First posted on arXiv 8 Aug 2023.

## Builds on (most cited first, 7 of 7)

- [Learning to Communicate with Deep Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/1605.06676/) (2016)
- [Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms](https://mlsanity.com/paper/1911.10635/) (2019)
- [Multi Type Mean Field Reinforcement Learning](https://mlsanity.com/paper/2002.02513/) (2020)
- [What Will 5G Be?](https://mlsanity.com/paper/1405.2957/) (2014)
- [Optimizing Space-Air-Ground Integrated Networks by Artificial Intelligence](https://mlsanity.com/paper/1808.01053/) (2018)
- [Software Defined Space-Air-Ground Integrated Vehicular Networks: Challenges and Solutions](https://mlsanity.com/paper/1703.02664/) (2017)
- [Designing and Implementing Future Aerial Communication Networks](https://mlsanity.com/paper/1602.05318/) (2016)

## Abstract (arXiv)

The Space-Air-Ground Integrated Network (SAGIN), integrating heterogeneous devices including low earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs), and ground users (GUs), holds significant promise for advancing smart city applications. However, resource management of the SAGIN is a challenge requiring urgent study in that inappropriate resource management will cause poor data transmission, and hence affect the services in smart cities. In this paper, we develop a comprehensive SAGIN system that encompasses five distinct communication links and propose an efficient cooperative multi-type multi-agent deep reinforcement learning (CMT-MARL) method to address the resource management issue. The experimental results highlight the efficacy of the proposed CMT-MARL, as evidenced by key performance indicators such as the overall transmission rate and transmission success rate. These results underscore the potential value and feasibility of future implementation of the SAGIN.