Data sharing games

TL;DR

This paper models data sharing interactions as a game inspired by the Iterated Prisoner's Dilemma, using multi-agent reinforcement learning to explore cooperation mechanisms among data producers and consumers.

Contribution

It introduces a formal game-theoretic model of data sharing and applies reinforcement learning to analyze strategies promoting cooperation.

Findings

Cooperation can emerge through opponent modeling by data consumers.

Regulators can incentivize cooperation by transferring utility.

Simulations demonstrate mechanisms for maximizing social utility.

Abstract

Data sharing issues pervade online social and economic environments. To foster social progress, it is important to develop models of the interaction between data producers and consumers that can promote the rise of cooperation between the involved parties. We formalize this interaction as a game, the data sharing game, based on the Iterated Prisoner's Dilemma and deal with it through multi-agent reinforcement learning techniques. We consider several strategies for how the citizens may behave, depending on the degree of centralization sought. Simulations suggest mechanisms for cooperation to take place and, thus, achieve maximum social utility: data consumers should perform some kind of opponent modeling, or a regulator should transfer utility between both players and incentivise them.