# Graphical Games for UAV Swarm Control Under Time-Varying Communication Networks

arXiv: https://arxiv.org/abs/2205.02203 · HTML: https://mlsanity.com/paper/2205.02203/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 May 2022.

## Built on by (most cited first, 1 of 1)

- [Physical Agentic AI: An Architecture for Orchestrating a Robot Crew with LLMs](https://mlsanity.com/paper/2608.22657/) (2026)

## Abstract (arXiv)

We propose a unified framework for coordinating Unmanned Aerial Vehicle (UAV) swarms operating under time-varying communication networks. Our framework builds on the concept of graphical games, which we argue provides a compelling paradigm to subsume the interaction structures found in networked UAV swarms thanks to the shared local neighborhood properties. We present a general-sum, factorizable payoff function for cooperative UAV swarms based on the aggregated local states and yield a Nash equilibrium for the stage games. Further, we propose a decomposition-based approach to solve stage-graphical games in a scalable and decentralized fashion by approximating virtual, mean neighborhoods. Finally, we discuss extending the proposed framework toward general-sum stochastic games by leveraging deep Q-learning and model-predictive control.