Welcome to the InfoSci Platform
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: © 2012 |Volume: 2 |Issue: 2 |Pages: 24
ISSN: 2155-5028|EISSN: 2155-5036|EISBN13: 9781466614062|DOI: 10.4018/ijsss.2012070103
Cite Article Cite Article

MLA

Diaf, Moussa, et al. "From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing." IJSSS vol.2, no.2 2012: pp.45-68. http://doi.org/10.4018/ijsss.2012070103

APA

Diaf, M., Hammouche, K., & Siarry, P. (2012). From the Real Ant to the Artificial Ant: Applications in Combinatorial Optimization, Data Clustering, Collective Robotics and Image Processing. International Journal of Signs and Semiotic Systems (IJSSS), 2(2), 45-68. http://doi.org/10.4018/ijsss.2012070103

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," International Journal of Signs and Semiotic Systems (IJSSS) 2, no.2: 45-68. http://doi.org/10.4018/ijsss.2012070103

Export Reference

Mendeley
Favorite Full-Issue Download

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 article, 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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.