On the Inapproximability of the Discrete Witsenhausen Problem

TL;DR

This paper proves that approximating solutions to the discrete Witsenhausen problem within any polynomial factor is NP-hard, highlighting the problem's computational intractability.

Contribution

It establishes the inapproximability of the discrete Witsenhausen problem within any polynomial factor, extending prior NP-completeness results.

Findings

Computing near-optimal strategies is NP-hard for the discrete Witsenhausen problem.

Approximation within a factor of $n^{2- ext{epsilon}}$ is NP-hard.

The problem remains computationally intractable even with bounded, integer-valued variables.

Abstract

We consider a discrete version of the Witsenhausen problem where all random variables are bounded and take on integer values. Our main goal is to understand the complexity of computing good strategies given the distributions for the initial state and second-stage noise as inputs to the problem. Following Papadimitriou and Tsitsiklis [1], who showed that computing the optimal solution is NP-complete, we construct a sequence of problem instances with the initial state uniform over a set of size $n$ and the noise uniform over a set of size at most $n^2$, such that finding a strategy whose cost is a multiplicative $n^{2-\epsilon}$ approximation to the optimal cost is NP-hard for any $\epsilon > 0$.