{"title":"随机环境下猜谜游戏的概率方法","authors":"A. P. Kovalevskii","doi":"10.1134/S1990478924010071","DOIUrl":null,"url":null,"abstract":"<p> The following game of two persons is formalized and solved in the paper. Player 1 is asked\na question. Player 2 knows the correct answer. Moreover, both players know all possible answers\nand their a priori probabilities. Player 2 must choose a subset of the given cardinality of deception\nanswers. Player 1 chooses one of the proposed answers. Player 1 wins one from Player 2 if he/she\nguessed the correct answer and zero otherwise. This game is reduced to a matrix game. However,\nthe game matrix is of large dimension, so the classical method based on solving a pair of dual\nlinear programming problems cannot be implemented for each individual problem. Therefore, it is\nnecessary to develop a method to radically reduce the dimension.\n</p><p>The whole set of such games is divided into two classes. The superuniform class of\ngames is characterized by the condition that the largest of the a priori probabilities is greater than\nthe probability of choosing an answer at random, and the subuniform class corresponds to the\nopposite inequality—each of the a priori probabilities when multiplied by the total number\nof answers presented to Player 1 does not exceed one. For each of these two classes, the solving\nthe extended matrix game is reduced to solving a linear programming problem of a much smaller\ndimension. For the subuniform class, the game is reformulated in terms of probability theory. The\ncondition for the optimality of a mixed strategy is formulated using the Bayes theorem. For the\nsuperuniform class, the solution of the game uses an auxiliary problem related to the subuniform\nclass. For both classes, we prove results on the probabilities of guessing the correct answer when\nusing optimal mixed strategies by both players. We present algorithms for obtaining these\nstrategies. The optimal mixed strategy of Player 1 is to choose an answer at random in the\nsubuniform class and to choose the most probable answer in the superuniform class. Optimal\nmixed strategies of Player 2 have much more complex structure.\n</p>","PeriodicalId":607,"journal":{"name":"Journal of Applied and Industrial Mathematics","volume":"18 1","pages":"70 - 80"},"PeriodicalIF":0.5800,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Probabilistic Approach to the Game of Guessing in a Random\\nEnvironment\",\"authors\":\"A. P. Kovalevskii\",\"doi\":\"10.1134/S1990478924010071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p> The following game of two persons is formalized and solved in the paper. Player 1 is asked\\na question. Player 2 knows the correct answer. Moreover, both players know all possible answers\\nand their a priori probabilities. Player 2 must choose a subset of the given cardinality of deception\\nanswers. Player 1 chooses one of the proposed answers. Player 1 wins one from Player 2 if he/she\\nguessed the correct answer and zero otherwise. This game is reduced to a matrix game. However,\\nthe game matrix is of large dimension, so the classical method based on solving a pair of dual\\nlinear programming problems cannot be implemented for each individual problem. Therefore, it is\\nnecessary to develop a method to radically reduce the dimension.\\n</p><p>The whole set of such games is divided into two classes. The superuniform class of\\ngames is characterized by the condition that the largest of the a priori probabilities is greater than\\nthe probability of choosing an answer at random, and the subuniform class corresponds to the\\nopposite inequality—each of the a priori probabilities when multiplied by the total number\\nof answers presented to Player 1 does not exceed one. For each of these two classes, the solving\\nthe extended matrix game is reduced to solving a linear programming problem of a much smaller\\ndimension. For the subuniform class, the game is reformulated in terms of probability theory. The\\ncondition for the optimality of a mixed strategy is formulated using the Bayes theorem. For the\\nsuperuniform class, the solution of the game uses an auxiliary problem related to the subuniform\\nclass. For both classes, we prove results on the probabilities of guessing the correct answer when\\nusing optimal mixed strategies by both players. We present algorithms for obtaining these\\nstrategies. The optimal mixed strategy of Player 1 is to choose an answer at random in the\\nsubuniform class and to choose the most probable answer in the superuniform class. Optimal\\nmixed strategies of Player 2 have much more complex structure.\\n</p>\",\"PeriodicalId\":607,\"journal\":{\"name\":\"Journal of Applied and Industrial Mathematics\",\"volume\":\"18 1\",\"pages\":\"70 - 80\"},\"PeriodicalIF\":0.5800,\"publicationDate\":\"2024-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied and Industrial Mathematics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1134/S1990478924010071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied and Industrial Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1134/S1990478924010071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
A Probabilistic Approach to the Game of Guessing in a Random
Environment
The following game of two persons is formalized and solved in the paper. Player 1 is asked
a question. Player 2 knows the correct answer. Moreover, both players know all possible answers
and their a priori probabilities. Player 2 must choose a subset of the given cardinality of deception
answers. Player 1 chooses one of the proposed answers. Player 1 wins one from Player 2 if he/she
guessed the correct answer and zero otherwise. This game is reduced to a matrix game. However,
the game matrix is of large dimension, so the classical method based on solving a pair of dual
linear programming problems cannot be implemented for each individual problem. Therefore, it is
necessary to develop a method to radically reduce the dimension.
The whole set of such games is divided into two classes. The superuniform class of
games is characterized by the condition that the largest of the a priori probabilities is greater than
the probability of choosing an answer at random, and the subuniform class corresponds to the
opposite inequality—each of the a priori probabilities when multiplied by the total number
of answers presented to Player 1 does not exceed one. For each of these two classes, the solving
the extended matrix game is reduced to solving a linear programming problem of a much smaller
dimension. For the subuniform class, the game is reformulated in terms of probability theory. The
condition for the optimality of a mixed strategy is formulated using the Bayes theorem. For the
superuniform class, the solution of the game uses an auxiliary problem related to the subuniform
class. For both classes, we prove results on the probabilities of guessing the correct answer when
using optimal mixed strategies by both players. We present algorithms for obtaining these
strategies. The optimal mixed strategy of Player 1 is to choose an answer at random in the
subuniform class and to choose the most probable answer in the superuniform class. Optimal
mixed strategies of Player 2 have much more complex structure.
期刊介绍:
Journal of Applied and Industrial Mathematics is a journal that publishes original and review articles containing theoretical results and those of interest for applications in various branches of industry. The journal topics include the qualitative theory of differential equations in application to mechanics, physics, chemistry, biology, technical and natural processes; mathematical modeling in mechanics, physics, engineering, chemistry, biology, ecology, medicine, etc.; control theory; discrete optimization; discrete structures and extremum problems; combinatorics; control and reliability of discrete circuits; mathematical programming; mathematical models and methods for making optimal decisions; models of theory of scheduling, location and replacement of equipment; modeling the control processes; development and analysis of algorithms; synthesis and complexity of control systems; automata theory; graph theory; game theory and its applications; coding theory; scheduling theory; and theory of circuits.