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The economics analysis of a Q -learning model of cooperation with punishment and risk taking preferences

机译:带有惩罚和冒险偏好的合作的Q学习模型的经济学分析

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The aim of this paper is to better understand how cooperation mechanisms work in the context of a Q-learning model. We apply a learning reinforcement model to analyse the conditions needed to have a stable cooperative equilibrium when people take part in a common project and could take advantages of free-riding. Our results show that a stable equilibrium can be reached thank to mechanisms of punishment, but the final result strongly depends on the risk-taking individuals' preferences. In particular, we find that the penalties will be effective only with people having high exploration rates,namely with people able to adapt their strategies and learn to cooperate. Otherwise, it is possible to have an unstable equilibrium with cooperation until individuals have a very high intrinsic motivation to cooperate, whatever the others do.
机译:本文的目的是更好地了解在Q学习模型的背景下合作机制如何工作。我们应用学习强化模型来分析人们参与共同项目并可以利用搭便车的优势时,要有一个稳定的合作平衡的条件。我们的结果表明,借助惩罚机制可以达到稳定的平衡,但最终结果很大程度上取决于冒险个人的偏好。尤其是,我们发现,只有对勘探率高的人,即对能够适应其策略并学会合作的人,处罚才有效。否则,可能存在不稳定的合作平衡,直到个体具有非常高的内在动力来进行合作,无论其他人做什么。

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