{"title":"随机多项式时间等于稍微随机多项式时间","authors":"U. Vazirani, V. Vazirani","doi":"10.1109/SFCS.1985.45","DOIUrl":null,"url":null,"abstract":"Random Polynomial Time (Rp) is currently considered to be the class of tractable computational problems. Here one assumes a source of truly random bits. However, the known sources of randomness are imperfect. They can be modeled as an adversary source, called slightly-random source. Slightlyrandom Polynomial Time (SRp) is the class of problems solvable in polynomial time using such a source. SRp is thus a more realistic definition of a tractable computational problem. In this paper we give an affirmative answer to the question \"is Rp = SRp?\" Our proof method is constructive: given an Rp algorithm for a problem, we show how to obtain an SRp algorithm for it. Studying the relationship between randomized and deterministic computation is currently an important issue. A central question here is \"is Rp = P?\" Our result may be a step towards answering this question.","PeriodicalId":296739,"journal":{"name":"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)","volume":"2 7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1985-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"101","resultStr":"{\"title\":\"Random polynomial time is equal to slightly-random polynomial time\",\"authors\":\"U. Vazirani, V. Vazirani\",\"doi\":\"10.1109/SFCS.1985.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Random Polynomial Time (Rp) is currently considered to be the class of tractable computational problems. Here one assumes a source of truly random bits. However, the known sources of randomness are imperfect. They can be modeled as an adversary source, called slightly-random source. Slightlyrandom Polynomial Time (SRp) is the class of problems solvable in polynomial time using such a source. SRp is thus a more realistic definition of a tractable computational problem. In this paper we give an affirmative answer to the question \\\"is Rp = SRp?\\\" Our proof method is constructive: given an Rp algorithm for a problem, we show how to obtain an SRp algorithm for it. Studying the relationship between randomized and deterministic computation is currently an important issue. A central question here is \\\"is Rp = P?\\\" Our result may be a step towards answering this question.\",\"PeriodicalId\":296739,\"journal\":{\"name\":\"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)\",\"volume\":\"2 7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1985-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"101\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SFCS.1985.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"26th Annual Symposium on Foundations of Computer Science (sfcs 1985)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SFCS.1985.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Random polynomial time is equal to slightly-random polynomial time
Random Polynomial Time (Rp) is currently considered to be the class of tractable computational problems. Here one assumes a source of truly random bits. However, the known sources of randomness are imperfect. They can be modeled as an adversary source, called slightly-random source. Slightlyrandom Polynomial Time (SRp) is the class of problems solvable in polynomial time using such a source. SRp is thus a more realistic definition of a tractable computational problem. In this paper we give an affirmative answer to the question "is Rp = SRp?" Our proof method is constructive: given an Rp algorithm for a problem, we show how to obtain an SRp algorithm for it. Studying the relationship between randomized and deterministic computation is currently an important issue. A central question here is "is Rp = P?" Our result may be a step towards answering this question.