{"title":"搜索理论中的最大熵原理","authors":"Aleksandr N. Prokaev","doi":"10.21638/11701/spbu10.2023.103","DOIUrl":null,"url":null,"abstract":"The paper considers the relationship between search theory and information theory. The traditional problem of search theory is to develop a search plan for a physical object in the sea or on land. The search plan has to develop the distribution of available search resources in such a way that the probability of detection the search object is to be maximum. The optimal solution is traditionally considered as so-called \"uniformly optimal search plan\", which provides a uniform distribution of the posterior probability of the location of the object as the search is conducted. At the same time, optimality simultaneously according to the criteria of maximum detection probability and equality of a posteriori probability is possible only for the exponential detection function, which is used most often in search theory. For other kinds of detection functions, the optimal solutions according to the specified criteria do not match. In this paper, the approach to this problem is considered on the basis of the maximum entropy principle. For a situation of discrete distribution, it is shown that, within the framework of information theory, the search problem has a simpler solution that does not depend on the kind of the detection function.","PeriodicalId":43738,"journal":{"name":"Vestnik Sankt-Peterburgskogo Universiteta Seriya 10 Prikladnaya Matematika Informatika Protsessy Upravleniya","volume":"55 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The maximum entropy principle in search theory\",\"authors\":\"Aleksandr N. Prokaev\",\"doi\":\"10.21638/11701/spbu10.2023.103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper considers the relationship between search theory and information theory. The traditional problem of search theory is to develop a search plan for a physical object in the sea or on land. The search plan has to develop the distribution of available search resources in such a way that the probability of detection the search object is to be maximum. The optimal solution is traditionally considered as so-called \\\"uniformly optimal search plan\\\", which provides a uniform distribution of the posterior probability of the location of the object as the search is conducted. At the same time, optimality simultaneously according to the criteria of maximum detection probability and equality of a posteriori probability is possible only for the exponential detection function, which is used most often in search theory. For other kinds of detection functions, the optimal solutions according to the specified criteria do not match. In this paper, the approach to this problem is considered on the basis of the maximum entropy principle. For a situation of discrete distribution, it is shown that, within the framework of information theory, the search problem has a simpler solution that does not depend on the kind of the detection function.\",\"PeriodicalId\":43738,\"journal\":{\"name\":\"Vestnik Sankt-Peterburgskogo Universiteta Seriya 10 Prikladnaya Matematika Informatika Protsessy Upravleniya\",\"volume\":\"55 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Vestnik Sankt-Peterburgskogo Universiteta Seriya 10 Prikladnaya Matematika Informatika Protsessy Upravleniya\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21638/11701/spbu10.2023.103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vestnik Sankt-Peterburgskogo Universiteta Seriya 10 Prikladnaya Matematika Informatika Protsessy Upravleniya","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21638/11701/spbu10.2023.103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
The paper considers the relationship between search theory and information theory. The traditional problem of search theory is to develop a search plan for a physical object in the sea or on land. The search plan has to develop the distribution of available search resources in such a way that the probability of detection the search object is to be maximum. The optimal solution is traditionally considered as so-called "uniformly optimal search plan", which provides a uniform distribution of the posterior probability of the location of the object as the search is conducted. At the same time, optimality simultaneously according to the criteria of maximum detection probability and equality of a posteriori probability is possible only for the exponential detection function, which is used most often in search theory. For other kinds of detection functions, the optimal solutions according to the specified criteria do not match. In this paper, the approach to this problem is considered on the basis of the maximum entropy principle. For a situation of discrete distribution, it is shown that, within the framework of information theory, the search problem has a simpler solution that does not depend on the kind of the detection function.
期刊介绍:
The journal is the prime outlet for the findings of scientists from the Faculty of applied mathematics and control processes of St. Petersburg State University. It publishes original contributions in all areas of applied mathematics, computer science and control. Vestnik St. Petersburg University: Applied Mathematics. Computer Science. Control Processes features articles that cover the major areas of applied mathematics, computer science and control.