Comparison of Two Swarm Intelligence Algorithms: From the Viewpoint of Learning

  • Guo-Sheng HaoEmail author
  • Ze-Hui Yi
  • Lin Wan
  • Qiu-Yi Shi
  • Ya-Li Liu
  • Gai-Ge Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10956)


It is always said that learning is at the core of intelligence. How does learning work in swarm intelligence algorithms (SIAs)? This paper tries to answer this question by analyzing the learning mechanisms in two new emerged swarm intelligence algorithms: Krill Herd algorithm, cuckoo search. Each algorithm generates new solutions by learning to explore/exploit the promising subspace. For the new solutions generators in each algorithm, we study the learning mechanism from the viewpoint of learning scheme includes learning subject, learning object, learning result and learning rule. Also we analyze their ability of exploration and exploitation. The above study not only enables theory researchers to get the similarities and differences among SIAs, but also helps them understand the integration of different SIAs together.


Swarm intelligence Learning mechanism Solution generators Exploitation Exploration 



Partly supported by the National Natural Science Foundation of China under Grant No. 61673196, 61503165, 61702237.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Guo-Sheng Hao
    • 1
    Email author
  • Ze-Hui Yi
    • 2
  • Lin Wan
    • 1
  • Qiu-Yi Shi
    • 1
  • Ya-Li Liu
    • 1
  • Gai-Ge Wang
    • 3
  1. 1.School of Computer Science and TechnologyJiangsu Normal UniversityXuzhouChina
  2. 2.School of Computer Science and TechnologyHuaiyin Normal UniversityHuai’anChina
  3. 3.College of Information Science and EngineeringOcean University of ChinaQingdaoChina

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