{"title":"(能源)政策可能很复杂:所以小心你的模拟器!","authors":"Eric Austin, J. Denzinger","doi":"10.1109/SSCI47803.2020.9308546","DOIUrl":null,"url":null,"abstract":"We present an Evolutionary Algorithm for testing the quality of policy simulators that also can be used for using the simulator for decision support. Our focus is on a simulator for energy policies for the Canadian province of Alberta. Our results show that the simulator works rather well in regard to its predictions of the environmental consequences of policies but seems to have serious flaws regarding its economic predictions.","PeriodicalId":413489,"journal":{"name":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"(Energy) Policies Can Be Complicated: So Be Careful With Your Simulators!\",\"authors\":\"Eric Austin, J. Denzinger\",\"doi\":\"10.1109/SSCI47803.2020.9308546\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an Evolutionary Algorithm for testing the quality of policy simulators that also can be used for using the simulator for decision support. Our focus is on a simulator for energy policies for the Canadian province of Alberta. Our results show that the simulator works rather well in regard to its predictions of the environmental consequences of policies but seems to have serious flaws regarding its economic predictions.\",\"PeriodicalId\":413489,\"journal\":{\"name\":\"2020 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Symposium Series on Computational Intelligence (SSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSCI47803.2020.9308546\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Symposium Series on Computational Intelligence (SSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSCI47803.2020.9308546","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
(Energy) Policies Can Be Complicated: So Be Careful With Your Simulators!
We present an Evolutionary Algorithm for testing the quality of policy simulators that also can be used for using the simulator for decision support. Our focus is on a simulator for energy policies for the Canadian province of Alberta. Our results show that the simulator works rather well in regard to its predictions of the environmental consequences of policies but seems to have serious flaws regarding its economic predictions.
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