# Differentially Private Formation Control: Privacy and Network Co-Design

arXiv: https://arxiv.org/abs/2205.13406 · HTML: https://mlsanity.com/paper/2205.13406/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 May 2022.

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

- [Deceptive Sequential Decision-Making via Regularized Policy Optimization](https://mlsanity.com/paper/2501.18803/) (2025)

## Abstract (arXiv)

Privacy in multi-agent control is receiving increased attention, though often a networked system and privacy protections are designed separately, which can harm performance. Therefore, this paper presents a co-design framework for networks and private controllers, and we apply it to private formation control. Agents' state trajectories are protected using differential privacy, and we quantify its impact by bounding the steady-state error for private formations. Then, we analyze tradeoffs between privacy level, system performance, and connectedness of the network's communication topology. These tradeoffs are used to formulate a co-design optimization framework to jointly design agents' communication topology and their privacy levels. Simulation results illustrate the success of this framework.