Probabilistic analysis and optimization of search algorithms

被引：0

作者：

Kralchev, Dobromir Pavlov ^{[1
]}

机构：

[1] Sofia Univ St Kliment Ohridski, Fac Math & Informat, James Bourchier Blvd 5, Sofia 1164, Bulgaria

来源：

ASIAN-EUROPEAN JOURNAL OF MATHEMATICS | 2024年 / 17卷 / 11期

关键词：

Stochastic search; backtracking; reflexive (self-monitoring) algorithms;

D O I：

10.1142/S1793557124500761

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

An interesting phenomenon about search algorithms is theoretically explained. Exponential optimization of running times has been achieved: the bigger the input size, the greater the acceleration. The optimization is equally applicable to exhaustive search, backtracking, and stochastic search.

引用

页数：10

共 6 条

[1]

Dimov D., 2001, INT C AUT INF SOF MA

[2]

Hooimeijer P., 2012, DISSERTATION

[3]

Jain S., 2022, ARXIV, DOI DOI 10.48550/ARXIV.2206.07286

[4] Solving Hard Computational Problems Efficiently: Asymptotic Parametric Complexity 3-Coloring Algorithm [J].

Martin H, Jose Antonio .

PLOS ONE, 2013, 8 (01)

[5]

Mu ZX, 2015, PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI), P367

[6]

Nobibon FT, 2010, LECT NOTES COMPUT SC, V6124, P229, DOI 10.1007/978-3-642-14355-7_24

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