Deterministic Team Problems with Signaling Incentive

TL;DR

This paper demonstrates that deterministic linear quadratic team decision problems with signaling incentives are tractable and can be efficiently solved using semi-definite programming under certain conditions.

Contribution

It establishes the optimality of linear decisions in deterministic team problems with signaling, providing a computationally efficient solution method.

Findings

Linear decisions are optimal under certain conditions.

Deterministic team problems are more tractable than stochastic ones.

Optimal solutions can be obtained via semi-definite programming.

Abstract

This paper considers linear quadratic team decision problems where the players in the team affect each other's information structure through their decisions. Whereas the stochastic version of the problem is well known to be complex with nonlinear optimal solutions that are hard to find, the deterministic counterpart is shown to be tractable. We show that under some assumptions on the weight matrix and the signaling channels, linear decisions are optimal and can be found efficiently by solving a semi-definite program.