Ant Colony Optimisation

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Author(s): Darryl Charles (University of Ulster, Ireland), Colin Fyfe (University of Paisley, UK), Daniel Livingstone (University of Paisley, UK)and Stephen McGlinchey (University of Paisley, UK)
Copyright: 2008
Pages: 22
Source title: Biologically Inspired Artificial Intelligence for Computer Games
Source Author(s)/Editor(s): Darryl Charles (University of Ulster, Ireland), Colin Fyfe (University of Paisley, UK), Daniel Livingstone (University of Paisley, UK)and Stephen McGlinchey (University of Paisley, UK)
DOI: 10.4018/978-1-59140-646-4.ch011

Keywords: Biologically-Inspired Computing / Medical Information Science Reference / Medical Technologies / Medicine & Healthcare

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Abstract

Ants are truly amazing creatures. Most species of ant are virtually blind; some of which have no vision at all, yet despite this, they are able to explore and find their way around their environment, discovering and ‘remembering’ routes between their nest and food sources. Ants exhibit complex social behaviours, with different roles assigned to different ants, and they are able to perform organised operations, even, for example, relocating their entire nest. Even a casual observer of an ant colony can see the efficiency and organisation with which they perform tasks such as foraging food. They are able to find and follow shortest paths between locations, negotiating obstacles between them, and this problem is an active area of interest in computer science, particularly in computer game AI.

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