{"title":"基于Agent的建模方法在复杂社会系统中的预测","authors":"C. Elsenbroich, J. Gareth Polhill","doi":"10.1080/13645579.2023.2152007","DOIUrl":null,"url":null,"abstract":"ABSTRACT Agent-based models (ABMs) have their origins in considerations of complexity science stipulating that many phenomena can be ‘grown from the bottom up’. Explicitly, this was expressed in Epstein & Axtell’s (1996) Growing Artificial Societies as the change from ‘Can you explain it?’ to ‘Can you grow it?’. In 2008, Epstein published an article entitled Why Model? in which he discussed his exasperation with people asking for predictions from ABM, pointing out that many other purposes to which it might be applied are more worthy of consideration than prediction, including explanation, improving data collection, testing theories and suggesting analogies. Fourteen years later, the debate about the predictive powers of ABM is still unresolved. This special issue presents the range of positions on ABM and prediction, tackling methodological, epistemological and pragmatic issues.","PeriodicalId":14272,"journal":{"name":"International Journal of Social Research Methodology","volume":"26 1","pages":"133 - 142"},"PeriodicalIF":3.0000,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Agent-based modelling as a method for prediction in complex social systems\",\"authors\":\"C. Elsenbroich, J. Gareth Polhill\",\"doi\":\"10.1080/13645579.2023.2152007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Agent-based models (ABMs) have their origins in considerations of complexity science stipulating that many phenomena can be ‘grown from the bottom up’. Explicitly, this was expressed in Epstein & Axtell’s (1996) Growing Artificial Societies as the change from ‘Can you explain it?’ to ‘Can you grow it?’. In 2008, Epstein published an article entitled Why Model? in which he discussed his exasperation with people asking for predictions from ABM, pointing out that many other purposes to which it might be applied are more worthy of consideration than prediction, including explanation, improving data collection, testing theories and suggesting analogies. Fourteen years later, the debate about the predictive powers of ABM is still unresolved. This special issue presents the range of positions on ABM and prediction, tackling methodological, epistemological and pragmatic issues.\",\"PeriodicalId\":14272,\"journal\":{\"name\":\"International Journal of Social Research Methodology\",\"volume\":\"26 1\",\"pages\":\"133 - 142\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2023-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Social Research Methodology\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1080/13645579.2023.2152007\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Social Research Methodology","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/13645579.2023.2152007","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Agent-based modelling as a method for prediction in complex social systems
ABSTRACT Agent-based models (ABMs) have their origins in considerations of complexity science stipulating that many phenomena can be ‘grown from the bottom up’. Explicitly, this was expressed in Epstein & Axtell’s (1996) Growing Artificial Societies as the change from ‘Can you explain it?’ to ‘Can you grow it?’. In 2008, Epstein published an article entitled Why Model? in which he discussed his exasperation with people asking for predictions from ABM, pointing out that many other purposes to which it might be applied are more worthy of consideration than prediction, including explanation, improving data collection, testing theories and suggesting analogies. Fourteen years later, the debate about the predictive powers of ABM is still unresolved. This special issue presents the range of positions on ABM and prediction, tackling methodological, epistemological and pragmatic issues.