Theoretical foundation for solving search problems by the method of maximum entropy

Aleksandr N. Prokaev
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Abstract

The traditional problem of search theory is to develop a search plan for a physical object in the sea or on land. Known algorithms for the optimal distribution of search resources mainly use the exponential detection function. If we consider the search problem more broadly — as a problem of searching for various information, then the detection function can differ significantly from the exponential one. In this case, the solutions obtained using traditional algorithms may be correct from the point of view of mathematics, but unacceptable from the point of view of logic. In this paper, this problem is solved on the basis of the maximum entropy principle. The theorems are proved, as well as their consequences for four types of detection functions, which make it possible to create algorithms for solving various search problems based on the principle of maximum entropy.
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最大熵法求解搜索问题的理论基础
搜索理论的传统问题是为海洋或陆地上的物理对象制定搜索计划。已知的搜索资源最优分配算法主要使用指数检测函数。如果我们将搜索问题更广泛地视为搜索各种信息的问题,那么检测函数可能与指数函数有很大不同。在这种情况下,使用传统算法得到的解从数学的角度来看可能是正确的,但从逻辑的角度来看是不可接受的。本文基于最大熵原理解决了这一问题。证明了这些定理,以及它们对四种检测函数的影响,这使得基于最大熵原理创建解决各种搜索问题的算法成为可能。
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