Decentralised Update Selection with Semi-Strategic Experts

TL;DR

This paper proposes a decentralized update selection mechanism inspired by blockchain governance, utilizing expert opinions with weighted approvals, ensuring stable equilibria and good approximation to optimal updates.

Contribution

It introduces a novel approval voting mechanism for decentralized update selection that accounts for expert expertise and provides equilibrium guarantees.

Findings

Mechanism always has approximate pure Nash equilibria.

Achieves constant factor approximation to the optimal update.

Extension maintains equilibria with adaptive expert weights.

Abstract

Motivated by governance models adopted in blockchain applications, we study the problem of selecting appropriate system updates in a decentralised way. Contrary to most existing voting approaches, we use the input of a set of motivated experts of varying levels of expertise. In particular, we develop an approval voting inspired selection mechanism through which the experts approve or disapprove the different updates according to their perception of the quality of each alternative. Given their opinions, and weighted by their expertise level, a single update is then implemented and evaluated, and the experts receive rewards based on their choices. We show that this mechanism always has approximate pure Nash equilibria and that these achieve a constant factor approximation with respect to the quality benchmark of the optimal alternative. Finally, we study the repeated version of the problem, where the weights of the experts are adjusted after each update, according to their performance. Under mild assumptions about the weights, the extension of our mechanism still has approximate pure Nash equilibria in this setting.