{"title":"齐次测度与多项式时不变量","authors":"L. Levin","doi":"10.1109/SFCS.1988.21919","DOIUrl":null,"url":null,"abstract":"The usual probability distributions are concentrated on strings that do not differ noticeably in any fundamental characteristics, except their informational size (Kolmogorov complexity). The formalization of this statement is given and shown to distinguish a class of homogeneous probability measures suggesting various applications. In particular, it could explain why the average case NP-completeness results are so measure-independent and could lead to their generalization to this wider and more invariant class of measures. It also demonstrates a sharp difference between recently discovered pseudorandom strings and the objects known before.<<ETX>>","PeriodicalId":113255,"journal":{"name":"[Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Homogeneous measures and polynomial time invariants\",\"authors\":\"L. Levin\",\"doi\":\"10.1109/SFCS.1988.21919\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The usual probability distributions are concentrated on strings that do not differ noticeably in any fundamental characteristics, except their informational size (Kolmogorov complexity). The formalization of this statement is given and shown to distinguish a class of homogeneous probability measures suggesting various applications. In particular, it could explain why the average case NP-completeness results are so measure-independent and could lead to their generalization to this wider and more invariant class of measures. It also demonstrates a sharp difference between recently discovered pseudorandom strings and the objects known before.<<ETX>>\",\"PeriodicalId\":113255,\"journal\":{\"name\":\"[Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SFCS.1988.21919\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SFCS.1988.21919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Homogeneous measures and polynomial time invariants
The usual probability distributions are concentrated on strings that do not differ noticeably in any fundamental characteristics, except their informational size (Kolmogorov complexity). The formalization of this statement is given and shown to distinguish a class of homogeneous probability measures suggesting various applications. In particular, it could explain why the average case NP-completeness results are so measure-independent and could lead to their generalization to this wider and more invariant class of measures. It also demonstrates a sharp difference between recently discovered pseudorandom strings and the objects known before.<>