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强化学习方法探索社会期望在利他行为中的作用。

A reinforcement learning approach to explore the role of social expectations in altruistic behavior.

机构信息

IdEst Advisory, Madrid, Spain.

Instituto de Investigación Tecnológica-Universidad Pontificia Comillas, Madrid, Spain.

出版信息

Sci Rep. 2023 Jan 31;13(1):1717. doi: 10.1038/s41598-023-28659-0.

Abstract

While altruism has been studied from a variety of standpoints, none of them has proven sufficient to explain the richness of nuances detected in experimentally observed altruistic behavior. On the other hand, the recent success of behavioral economics in linking expectation formation to key behaviors in complex societies hints to social expectations having a key role in the emergence of altruism. This paper proposes an agent-based model based upon the Bush-Mosteller reinforcement learning algorithm in which agents, subject to stimuli derived from empirical and normative expectations, update their aspirations (and, consequently, their future cooperative behavior) after playing successive rounds of the Dictator Game. The results of the model are compared with experimental results. Such comparison suggests that a stimuli model based on empirical and normative expectations, such as the one presented in this work, has considerable potential for capturing the cognitive-behavioral processes that shape decision-making in contexts where cooperative behavior is relevant.

摘要

虽然利他主义已经从各种角度进行了研究,但没有一种角度足以解释在实验观察到的利他行为中发现的细微差别之丰富性。另一方面,行为经济学最近在将期望形成与复杂社会中的关键行为联系起来方面取得的成功表明,社会期望在利他主义的出现中起着关键作用。本文提出了一个基于 Bush-Mosteller 强化学习算法的基于代理的模型,其中代理根据来自经验和规范期望的刺激更新他们的愿望(因此,他们未来的合作行为),在玩了几轮独裁游戏之后。模型的结果与实验结果进行了比较。这种比较表明,基于经验和规范期望的刺激模型,如本文所提出的,具有很大的潜力,可以捕捉到在合作行为相关的情境中塑造决策的认知行为过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4e4/9889354/488fc2b094ef/41598_2023_28659_Fig1_HTML.jpg

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