# Control of Multi-Layer Mobile Autonomous Systems in Adversarial Environments: A Games-in-Games Approach

arXiv: https://arxiv.org/abs/1912.04082 · HTML: https://mlsanity.com/paper/1912.04082/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Dec 2019.

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

- [Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threats](https://mlsanity.com/paper/2507.10621/) (2025)

## Abstract (arXiv)

Mobile autonomous system (MAS) becomes pervasive especially in the vehicular and robotic networks. Multiple heterogeneous MAS networks can be integrated together as a multi-layer MAS network to offer holistic services. The network connectivity of multi-layer MAS plays an important role in the information exchange between agents within and across different layers of the network. In this paper, we establish a games-in-games framework to capture the uncoordinated nature of decision makings under adversarial environment at different layers. Specifically, each network operator controls the mobile agents in his own subnetwork and designs a secure strategy to maximize the global network connectivity by considering the behavior of jamming attackers that aim to disconnect the network. The solution concept of meta-equilibrium is proposed to characterize the system-of-systems behavior of the autonomous agents. For online implementation of the control, we design a resilient algorithm that improves the network algebraic connectivity iteratively. We show that the designed algorithm converges to a meta-equilibrium asymptotically. Finally, we use case studies of a two-layer MAS network to corroborate the security and agile resilience of the network controlled by the proposed strategy.