{"title":"多模式思维","authors":"S. Page","doi":"10.1109/WSC.2016.7822072","DOIUrl":null,"url":null,"abstract":"Models help us to understand, explain, predict, and act. They do so by simplifying reality or by constructing artificial analogs. As a result, any one model by be insufficient to capture the complexity of a process. By applying ensembles of diverse models, we can reach deeper understanding, make better predictions, take wiser actions, implement better designs, and reveal multiple logics. This many to one approach offers the possibility of near truth exists at what Richard Levins has called “the intersection of independent lies.”","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"312 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Many Model Thinking\",\"authors\":\"S. Page\",\"doi\":\"10.1109/WSC.2016.7822072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Models help us to understand, explain, predict, and act. They do so by simplifying reality or by constructing artificial analogs. As a result, any one model by be insufficient to capture the complexity of a process. By applying ensembles of diverse models, we can reach deeper understanding, make better predictions, take wiser actions, implement better designs, and reveal multiple logics. This many to one approach offers the possibility of near truth exists at what Richard Levins has called “the intersection of independent lies.”\",\"PeriodicalId\":367269,\"journal\":{\"name\":\"2016 Winter Simulation Conference (WSC)\",\"volume\":\"312 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Winter Simulation Conference (WSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSC.2016.7822072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC.2016.7822072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Models help us to understand, explain, predict, and act. They do so by simplifying reality or by constructing artificial analogs. As a result, any one model by be insufficient to capture the complexity of a process. By applying ensembles of diverse models, we can reach deeper understanding, make better predictions, take wiser actions, implement better designs, and reveal multiple logics. This many to one approach offers the possibility of near truth exists at what Richard Levins has called “the intersection of independent lies.”