Infinitely repeated games with self-control: A dual-self interpretation of the Monks Story.

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Title: Infinitely repeated games with self-control: A dual-self interpretation of the Monks Story.
Authors: Wang, W.1 wangw.10@sem.tsinghua.edu.cn, Zheng, J.1 zhengjie@sem.tsinghua.edu.cn
Source: Automation & Remote Control. Mar2015, Vol. 76 Issue 3, p521-534. 14p.
Subjects: Chinese proverbs, Reality in literature, Folk literature, Self-control, Personnel management, Themes in literature
Abstract: In this paper, we use The Monks Story, a famous traditional Chinese proverb, as an example to illustrate the practicality of our model on the matters in reality. The Monks Story is typically used in literature that is related to marketing, human resource, and management aspects. However, in our paper, we look at the Monks Story from a different perspective: we assume that the number of players does not change over time and examine how players' behaviors evolve over time. Our analysis of this story is focused on how individual player as a dual-self individual makes decisions when interacting with other players. We analyze the story and compare the results under three scenarios: history-independent strategy case, history-dependent strategy case and dual-self approach. [ABSTRACT FROM AUTHOR]
Copyright of Automation & Remote Control is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Infinitely repeated games with self-control: A dual-self interpretation of the Monks Story.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+W%2E%22">Wang, W.</searchLink><relatesTo>1</relatesTo><i> wangw.10@sem.tsinghua.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zheng%2C+J%2E%22">Zheng, J.</searchLink><relatesTo>1</relatesTo><i> zhengjie@sem.tsinghua.edu.cn</i>
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  Data: <searchLink fieldCode="DE" term="%22Chinese+proverbs%22">Chinese proverbs</searchLink><br /><searchLink fieldCode="DE" term="%22Reality+in+literature%22">Reality in literature</searchLink><br /><searchLink fieldCode="DE" term="%22Folk+literature%22">Folk literature</searchLink><br /><searchLink fieldCode="DE" term="%22Self-control%22">Self-control</searchLink><br /><searchLink fieldCode="DE" term="%22Personnel+management%22">Personnel management</searchLink><br /><searchLink fieldCode="DE" term="%22Themes+in+literature%22">Themes in literature</searchLink>
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  Data: In this paper, we use The Monks Story, a famous traditional Chinese proverb, as an example to illustrate the practicality of our model on the matters in reality. The Monks Story is typically used in literature that is related to marketing, human resource, and management aspects. However, in our paper, we look at the Monks Story from a different perspective: we assume that the number of players does not change over time and examine how players' behaviors evolve over time. Our analysis of this story is focused on how individual player as a dual-self individual makes decisions when interacting with other players. We analyze the story and compare the results under three scenarios: history-independent strategy case, history-dependent strategy case and dual-self approach. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Automation & Remote Control is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1134/S0005117915030169
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