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Friendly-rivalry solution to the iterated n-person public-goods game

 
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Manage episode 288621271 series 2902310
内容由MultiModal LLC and Multimodal LLC提供。所有播客内容(包括剧集、图形和播客描述)均由 MultiModal LLC and Multimodal LLC 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.05.237552v1?rss=1 Authors: Murase, Y., Baek, S. K. Abstract: Repeated interaction promotes cooperation among rational individuals under the shadow of future, but it is hard to maintain cooperation when a large number of error-prone individuals are involved. One way to construct a cooperative Nash equilibrium is to find a `friendly rivalry' strategy, which aims at full cooperation but never allows the co-players to be better off. Recently it has been shown that for the iterated Prisoner's Dilemma in the presence of error, a friendly rival can be designed with the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish defection, recover cooperation if you find a chance, and defect in all the other circumstances. In this work, we construct such a friendly-rivalry strategy for the iterated n -person public-goods game by generalizing those five rules. The resulting strategy makes a decision with referring to the previous m=2n-1 rounds. A friendly-rivalry strategy inherently has evolutionary robustness in the sense that no mutant strategy has higher fixation probability in this population than that of neutral drift, and our evolutionary simulation indeed shows excellent performance of the proposed strategy in a broad range of environmental conditions. Copy rights belong to original authors. Visit the link for more info
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已归档的系列专辑 ("不活跃的收取点" status)

When? This feed was archived on December 15, 2021 15:07 (2+ y ago). Last successful fetch was on March 29, 2021 12:55 (3y ago)

Why? 不活跃的收取点 status. 我们的伺服器已尝试了一段时间,但仍然无法截取有效的播客收取点

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 288621271 series 2902310
内容由MultiModal LLC and Multimodal LLC提供。所有播客内容(包括剧集、图形和播客描述)均由 MultiModal LLC and Multimodal LLC 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.05.237552v1?rss=1 Authors: Murase, Y., Baek, S. K. Abstract: Repeated interaction promotes cooperation among rational individuals under the shadow of future, but it is hard to maintain cooperation when a large number of error-prone individuals are involved. One way to construct a cooperative Nash equilibrium is to find a `friendly rivalry' strategy, which aims at full cooperation but never allows the co-players to be better off. Recently it has been shown that for the iterated Prisoner's Dilemma in the presence of error, a friendly rival can be designed with the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish defection, recover cooperation if you find a chance, and defect in all the other circumstances. In this work, we construct such a friendly-rivalry strategy for the iterated n -person public-goods game by generalizing those five rules. The resulting strategy makes a decision with referring to the previous m=2n-1 rounds. A friendly-rivalry strategy inherently has evolutionary robustness in the sense that no mutant strategy has higher fixation probability in this population than that of neutral drift, and our evolutionary simulation indeed shows excellent performance of the proposed strategy in a broad range of environmental conditions. Copy rights belong to original authors. Visit the link for more info
  continue reading

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