# LQG Information Design

arXiv: https://arxiv.org/abs/2312.09479 · HTML: https://mlsanity.com/paper/2312.09479/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Dec 2023.

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

- [Semantic Rate Distortion and Posterior Design: Compute Constraints, Multimodality, and Strategic Inference](https://mlsanity.com/paper/2602.03949/) (2026)

## Abstract (arXiv)

This paper addresses information design in a workhorse model of network games, where agents have linear best responses, the information designer maximizes a quadratic objective, and the payoff-relevant state follows a multivariate Gaussian distribution. We formulate the problem as a semidefinite program and establish strong duality to characterize the optimal information structure. A necessary and sufficient condition for optimality is given by a simple linear relationship between the induced equilibrium strategy profile and the state. Leveraging this characterization, we show that the state is fully revealed in an aggregative form for welfare maximization, while individual agents may remain only partially informed. When agent roles are interchangeable, the optimal information structure inherits the same degree of symmetry, which facilitates computation. In such cases, we show that the optimal amount of information revealed to each agent is closely linked to the network's chromatic number.