A Probabilistic Approach to the Game of Guessing in a Random Environment

A. P. Kovalevskii
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引用次数: 0

Abstract

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.

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摘要 本文将下列两人博弈形式化并求解。棋手 1 被问了一个问题。玩家 2 知道正确答案。此外,两人都知道所有可能的答案及其先验概率。玩家 2 必须从给定数量的欺骗答案中选择一个子集。玩家 1 从提出的答案中选择一个。如果玩家 1 猜中了正确答案,他/她将从玩家 2 处赢取 1 分,否则赢取 0 分。这个博弈可以简化为矩阵博弈。然而,博弈矩阵的维度很大,因此基于求解一对双线性规划问题的经典方法无法在每个问题上实现。因此,有必要开发一种从根本上降低维数的方法。超均匀类博弈的特点是最大的先验概率大于随机选择答案的概率,而亚均匀类博弈则对应于相反的不等式--每个先验概率乘以玩家 1 得到的答案总数不超过 1。对于这两个类别中的每一类,扩展矩阵博弈的求解都简化为求解一个维度更小的线性规划问题。对于亚均匀类,博弈用概率论重新表述。利用贝叶斯定理提出了混合策略最优的条件。对于超均匀类,博弈的求解使用了与亚均匀类相关的辅助问题。对于这两类博弈,我们都证明了博弈双方使用最优混合策略时猜中正确答案的概率。我们提出了获得这些策略的算法。玩家 1 的最优混合策略是在次均匀类中随机选择一个答案,并在超均匀类中选择最可能的答案。棋手 2 的最优混合策略结构要复杂得多。
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来源期刊
Journal of Applied and Industrial Mathematics
Journal of Applied and Industrial Mathematics Engineering-Industrial and Manufacturing Engineering
CiteScore
1.00
自引率
0.00%
发文量
16
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.
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