Data sharing games
This addresses data sharing issues in social and economic contexts, but it is incremental as it applies existing game theory and reinforcement learning to a specific domain.
The paper tackles the problem of fostering cooperation between data producers and consumers in online environments by formalizing it as a data sharing game based on the Iterated Prisoner's Dilemma and using multi-agent reinforcement learning. Simulations suggest that cooperation and maximum social utility can be achieved through opponent modeling by consumers or utility transfers by a regulator.
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.