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| An introduction to Ant Colony Algorithms |
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by an obstacle appearing somewhere in the path? When the ants reach the obstacle they will randomly choose some way around it(right, left, over or under). If we assume that the only way around the obstacle is either right or left, we can safely assume that approximately half of the ants will go right and the other half left, as illustrated below.

The ants that happen to pick the shorter path will obviously create a strong trail of pheromone a lot faster than the ones choosing a longer path(see below). This will cause more and more ants to choose the shorter path until eventually all ants have found the shortest path.

Ant Colony Algorithms attempt somehow to apply similar techniques in order to solve real life problems.
The main idea is to use repeated and often recurrent simulations of artificial ants
(mobile agents inspired by
real ant behaviour) to generate new solutions to the problem at hand. The ants use information collected during
past simulations to direct their search and this information is available and modified through the environment.
Many different artificial ant algorithms have been implemented and no universal definition of an artificial
ant fits them all. In the next section we will take a look at an example where an artificial ant colony solves
the travelling salesman problem.
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Comments : Johann Bragi Fjalldal Last modified: Mon Feb 15 09:43:17 GMT 1999