Swarm intelligence-based bio-inspired algorithms

被引：1

作者：

Bozhinoski, Darko ^{[1
]}

机构：

[1] Univ Libre Bruxelles, IRIDIA, Brussels, Belgium

来源：

PROCEEDINGS OF THE 2024 IEEE/ACM 19TH SYMPOSIUM ON SOFTWARE ENGINEERING FOR ADAPTIVE AND SELF-MANAGING SYSTEMS, SEAMS 2024 | 2024年

关键词：

self-adaptive systems; swarm intelligence; software engineering; OPTIMIZATION;

D O I：

10.1145/3643915.3644086

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Swarm-based algorithms are one of the most popular bio-inspired algorithms inspired by animals' collective behavior. In this position paper, I discuss the benefits of how the self-adaptive community could benefit from considering bio-inspired algorithms in designing self-adaptive systems. I focus specifically on swarm-based algorithms where I discuss three main benefits: (i) utilizing swarm intelligence techniques for parameter optimization of the utility function in the design phase; (ii) enhancing MAPE-K loop with swarm-inspired algorithms in the run-time phase; (iii) emergent robust behavior as a byproduct of simple interactions among individual components.

引用

页码：105 / 106

页数：2

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