Buggy Pinball: A Novel Single-point Meta-heuristic for Global Continuous Optimization

被引：0

作者：

Lymperakis, Vasileios ^{[1
]}

Panagopoulos, Athanasios Aris ^{[2
]}

机构：

[1] Tech Univ Crete, Khania, Greece

[2] Calif State Univ Fresno, Fresno, CA 93740 USA

来源：

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2022, PT II | 2023年 / 13589卷

关键词：

ALGORITHM;

D O I：

10.1007/978-3-031-23480-4_22

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work, we propose a fundamentally novel single-point meta-heuristic designed for continuous optimization. Our algorithm continuously improves on a solution via a trajectory-based search inspired by the pinball arcade game in an anytime optimization manner. We evaluate our algorithm against widely employed meta-heuristics on several standard test-bed functions and various dimensions. Our algorithm exhibits high precision, and superior accuracy compared to the benchmark, especially when complex configuration spaces are considered.

引用

页码：264 / 276

页数：13

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