分布式系统的通用退出机制

IF 1.6 4区计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Artificial Life Pub Date : 2023-03-01 DOI:10.1162/artl_a_00393

Larry Bull;Haixia Liu

{"title":"分布式系统的通用退出机制","authors":"Larry Bull;Haixia Liu","doi":"10.1162/artl_a_00393","DOIUrl":null,"url":null,"abstract":"This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global control is further explored. The conditions under which the beneficial distributed control emerges are more clearly identified, and the reason for the benefit over traditional global control is suggested as a generally applicable dropout mechanism to improve learning in such systems.","PeriodicalId":55574,"journal":{"name":"Artificial Life","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Generalised Dropout Mechanism for Distributed Systems\",\"authors\":\"Larry Bull;Haixia Liu\",\"doi\":\"10.1162/artl_a_00393\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global control is further explored. The conditions under which the beneficial distributed control emerges are more clearly identified, and the reason for the benefit over traditional global control is suggested as a generally applicable dropout mechanism to improve learning in such systems.\",\"PeriodicalId\":55574,\"journal\":{\"name\":\"Artificial Life\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Life\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10301848/\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Life","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10301848/","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}

引用次数: 0

摘要

这封信使用NK模型的修改形式来探索分布式控制的各个方面。特别是，先前的结果表明，在整个系统中使用动态形成的子群比全局控制更有效。更清楚地识别了有益的分布式控制出现的条件，并提出了优于传统全局控制的原因，即普遍适用的辍学机制，以改善此类系统的学习。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Generalised Dropout Mechanism for Distributed Systems

This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global control is further explored. The conditions under which the beneficial distributed control emerges are more clearly identified, and the reason for the benefit over traditional global control is suggested as a generally applicable dropout mechanism to improve learning in such systems.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Artificial Life 工程技术-计算机：理论方法

CiteScore

4.70

自引率

7.70%

发文量

审稿时长

>12 weeks

期刊介绍： Artificial Life, launched in the fall of 1993, has become the unifying forum for the exchange of scientific information on the study of artificial systems that exhibit the behavioral characteristics of natural living systems, through the synthesis or simulation using computational (software), robotic (hardware), and/or physicochemical (wetware) means. Each issue features cutting-edge research on artificial life that advances the state-of-the-art of our knowledge about various aspects of living systems such as: Artificial chemistry and the origins of life Self-assembly, growth, and development Self-replication and self-repair Systems and synthetic biology Perception, cognition, and behavior Embodiment and enactivism Collective behaviors of swarms Evolutionary and ecological dynamics Open-endedness and creativity Social organization and cultural evolution Societal and technological implications Philosophy and aesthetics Applications to biology, medicine, business, education, or entertainment.