Nature-Inspired Swarm Intelligence and Its Applications

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Sangita Roy 1,* Samir Biswas 2 Sheli Sinha Chaudhuri 2

1. ECE Department, Narula Institute of Technology, WBUT, India

2. ETCE Department, Jadavpur University, India

* Corresponding author.


Received: 17 Sep. 2014 / Revised: 6 Oct. 2014 / Accepted: 2 Nov. 2014 / Published: 8 Dec. 2014

Index Terms

Stigmergic, pheromone, forage, AI (Artificial Intelligence), metaheuristic, emergence, SO (Self Organization), swarm intelligence.


In 1989 Gerardo Beni and Jing Wang first proposed the name “Swarm Intelligence” in their paper “Swarm Intelligence in Cellular Robotic Systems”. Some remarkable observations of different researchers are studied in this paper, like the proximity principle, the quality principle, the principle of diverse response, the principle of stability, the principle of adaptability. To enhance the capabilities of robot and different systems, researchers started to exploit the behavior of natural systems. Swarm groups are governed by three rules, move in the same direction as your neighbor, remain close to your neighbor, and avoid collision with your neighbor .Characteristics of swarm groups are emergence and stigmergy. Different insects like ants, wasps, termites carry out a work locally for global goal with sufficient flexibility as they are not controlled centrally. In this paper the existing research works are analysed to show the behavior in social insects by using self-organization, positive feedback, negative feedback, amplification of fluctuation, multiple interactions. It has also been observed that these insects are almost blind and memoryless, still they communicate indirectly among themselves for stigmergic effect by using pheromone. Implementation of swarm intelligence in robotics i.e., swarm robots are narrated. The limitations of swarm robots as well as factors behind the success of swarm robotics have also been encompassed. Finally authors focus on swarm robots applications in telecommunication fields, civil engineering and digital image processing.

Cite This Paper

Sangita Roy, Samir Biswas, Sheli Sinha Chaudhuri, "Nature-Inspired Swarm Intelligence and Its Applications", International Journal of Modern Education and Computer Science (IJMECS), vol.6, no.12, pp.55-65, 2014. DOI:10.5815/ijmecs.2014.12.08


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