Intrinsically motivated reinforcement learning in socio-economic systems: The dynamical analysis

A. Zgonnikov, I. Lubashevsky
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Abstract

We conduct a theoretical analysis of the effects of intrinsic motivation on learning dynamics. We study a simple example of a single agent adapting to unknown environment; the agent is biased by the desire to take those actions she has little information about. We show that the intrinsic motivation may induce the instability (namely, periodic oscillations) of the learning process that is stable in case of rational agent. Most interestingly, we discover that the opposite effect may arise as well: the cyclic learning dynamics is stabilized by high levels of agent intrinsic motivation. Based on the presented results we argue that the effects of human intrinsic motivation in particular and bounded rationality in general may appear dominant in complex socio-economic systems and therefore deserve much attention in the formal models of such systems.
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社会经济系统中的内在动机强化学习:动态分析
我们对内在动机对学习动力的影响进行了理论分析。我们研究了一个简单的单智能体适应未知环境的例子;行为人会因为想要采取她所知甚少的行动而产生偏见。我们证明了内在动机可能导致学习过程的不稳定性(即周期性振荡),而在理性智能体的情况下,学习过程是稳定的。最有趣的是,我们发现相反的效果也可能出现:高水平的代理内在动机稳定了循环学习动态。基于所提出的结果,我们认为人类内在动机的影响,特别是有限理性的影响,可能在复杂的社会经济系统中占主导地位,因此在这些系统的正式模型中值得关注。
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