Swarm Intelligence

杂志介绍

Swarm Intelligence杂志介绍

《Swarm Intelligence》是一本以English为主的未开放获取国际优秀期刊，中文名称群体智能，本刊主要出版、报道计算机科学-COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为2.1，最新CiteScore 指数为5.7。

本刊近期中国学者发表的论文主要有：

• Long-term pattern formation and maintenance for battery-powered robots

  Author: Guannan Li, Ivan Svogor, Giovanni Beltrame

• Behaviour Based Coverage Controller

  Author: oyekanjohn

• Behaviour Based Coverage Controller

  Author: oyekanjohn

英文介绍

Swarm Intelligence杂志英文介绍

Swarm Intelligence is the principal peer-reviewed publication dedicated to reporting on research

and developments in the multidisciplinary field of swarm intelligence. The journal publishes

original research articles and occasional review articles on theoretical, experimental and/or

practical aspects of swarm intelligence. All articles are published both in print and in electronic

form. There are no page charges for publication. Swarm Intelligence is published quarterly.

The field of swarm intelligence deals with systems composed of many individuals that coordinate

using decentralized control and self-organization. In particular, it focuses on the collective

behaviors that result from the local interactions of the individuals with each other and with their

environment. It is a fast-growing field that encompasses the efforts of researchers in multiple

disciplines, ranging from ethology and social science to operations research and computer

engineering.

Swarm Intelligence will report on advances in the understanding and utilization of swarm

intelligence systems, that is, systems that are based on the principles of swarm intelligence. The

following subjects are of particular interest to the journal:

• modeling and analysis of collective biological systems such as social insect colonies, flocking

vertebrates, and human crowds as well as any other swarm intelligence systems;

• application of biological swarm intelligence models to real-world problems such as distributed

computing, data clustering, graph partitioning, optimization and decision making;

• theoretical and empirical research in ant colony optimization, particle swarm optimization,

swarm robotics, and other swarm intelligence algorithms.