A new swarm intelligence coordination model inspired by collective prey retrieval and its application to image alignment

  • Authors:

  • G. Da San Martino;F. A. Cardillo;A. Starita

  • Affiliations:

  • Dept. of Pure and Applied Mathematics, University of Padova, Italy;Dept. of Computer Science, University of Pisa, Italy;Dept. of Computer Science, University of Pisa, Italy

  • Venue:
  • PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
  • Year:
  • 2006

  • Front Matter

    Proceedings of the 2009 conference on Computational Intelligence and Bioengineering: Essays in Memory of Antonina Starita

  • A Swarm-Based Learning Method Inspired by Social Insects

    ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence

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Abstract

Swarm Intelligence is the emergent collective intelligence of groups of simple agents acting almost independently. Algorithms following this paradigm have many desirable properties: flexibility, decentralized control, robustness, and fault tolerance. This paper presents a novel agent coordination model inspired by the way ants collectively transport large preys. In our model a swarm of agents, each having a different destination to reach, moves with no centralized control in the direction indicated by the majority of agents keeping its initial shape. The model is used to build an algorithm for the problems of image alignment and image matching. The novelty of the approach and its effectiveness are discussed.