Swarm Intelligence: Past, Present and Future
Xin-She Yang, Suash Deb, Yuxin Zhao, Simon Fong, Xingshi He

TL;DR
This paper reviews the evolution, current state, and future prospects of swarm intelligence algorithms, analyzing their properties and connections with self-organization to guide future research in optimization.
Contribution
It offers a comprehensive analysis of SI algorithms, highlighting their characteristics, mathematical foundations, and open challenges, along with future research directions.
Findings
SI algorithms are linked to self-organization principles.
Mathematical and qualitative analyses reveal key properties of SI.
Open problems and future directions are identified.
Abstract
Many optimization problems in science and engineering are challenging to solve, and the current trend is to use swarm intelligence (SI) and SI-based algorithms to tackle such challenging problems. Some significant developments have been made in recent years, though there are still many open problems in this area. This paper provides a short but timely analysis about SI-based algorithms and their links with self-organization. Different characteristics and properties are analyzed here from both mathematical and qualitative perspectives. Future research directions are outlined and open questions are also highlighted.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
