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From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing

From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing

Moussa Diaf, Kamal Hammouche, Patrick Siarry
Copyright: © 2010 |Pages: 25
ISBN13: 9781605667058|ISBN10: 1605667056|ISBN13 Softcover: 9781616924188|EISBN13: 9781605667065
DOI: 10.4018/978-1-60566-705-8.ch013
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MLA

Diaf, Moussa, et al. "From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing." Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, edited by Raymond Chiong, IGI Global, 2010, pp. 298-322. https://doi.org/10.4018/978-1-60566-705-8.ch013

APA

Diaf, M., Hammouche, K., & Siarry, P. (2010). From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing. In R. Chiong (Ed.), Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering (pp. 298-322). IGI Global. https://doi.org/10.4018/978-1-60566-705-8.ch013

Chicago

Diaf, Moussa, Kamal Hammouche, and Patrick Siarry. "From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing." In Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, edited by Raymond Chiong, 298-322. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-705-8.ch013

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Abstract

Biological studies highlighting the collective behavior of ants in fulfilling various tasks by using their complex indirect communication process have constituted the starting point for many physical systems and various ant colony algorithms. Each ant colony is considered as a superorganism which operates as a unified entity made up of simple agents. These agents (ants) interact locally with one another and with their environment, particularly in finding the shortest path from the nest to food sources without any centralized control dictating the behavior of individual agents. It is this coordination mechanism that has inspired researchers to develop plenty of metaheuristic algorithms in order to find good solutions for NP-hard combinatorial optimization problems. In this chapter, the authors give a biological description of these fascinating insects and their complex indirect communication process. From this rich source of inspiration for researchers, the authors show how, through the real ant, artificial ant is modeled and applied in combinatorial optimization, data clustering, collective robotics, and image processing.

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