Regularized Stochastic Team Problems

TL;DR

This paper introduces regularized stochastic team problems, proves the existence of a unique optimal decision rule, and provides an algorithm to compute it with performance bounds.

Contribution

It presents the first analysis of regularized stochastic team problems, establishing existence, uniqueness, and a distributed algorithm for optimal strategies.

Findings

Unique fixed point of best response operator exists.

Distributed algorithm converges to the optimal regularized decision rule.

Performance bounds relate regularized and original problems.

Abstract

In this paper, we introduce regularized stochastic team problems. Under mild assumptions, we prove that there exists an unique fixed point of the best response operator, where this unique fixed point is the optimal regularized team decision rule. Then, we establish an asynchronous distributed algorithm to compute this optimal strategy. We also provide a bound that shows how the optimal regularized team decision rule performs in the original stochastic team problem.