Swarm intelligence-based bio-inspired algorithms

被引：0
|
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
收藏
页码：105 / 106
页数：2
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