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.
翻译:数据共享问题遍布在线社会和经济环境。为了促进社会进步,必须开发数据生产者和消费者互动模式,以促进有关各方之间合作的兴起。我们将这种互动作为一种游戏,即数据共享游戏正式化,以迭代囚犯的困境为基础,并通过多试剂强化学习技术加以处理。我们考虑了公民如何行为的若干战略,这取决于所寻求的集中程度。模拟表明将开展合作的机制,从而实现最大程度的社会效用:数据消费者应发挥某种对手模型的作用,或者监管者应在参与者之间转让效用并激励他们。