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|Title: ||Understanding how Knowledge is exploited in Ant Algorithms|
|Authors: ||McCallum, Thomas Edward Reid|
|Supervisor(s): ||Levine, John|
|Issue Date: ||Dec-2005|
|Publisher: ||University of Edinburgh. College of Science and Engineering. School of Informatics.|
|Abstract: ||Ant algorithms were first written about in 1991 and since then they have been applied
to many problems with great success. During these years the algorithms themselves
have been modified for improved performance and also been influenced by research in
other fields. Since the earliest Ant algorithms, heuristics and local search have been
the primary knowledge sources. This thesis asks the question "how is knowledge used
in Ant algorithms?"
To answer this question three Ant algorithms are implemented. The first is the Graph based
Ant System (GBAS), a theoretical model not yet implemented, and the others
are two influential algorithms, the Ant System and Max-Min Ant System. A comparison
is undertaken to show that the theoretical model empirically models what happens
in the other two algorithms. Therefore, this chapter explores whether different
pheromone matrices (representing the internal knowledge) have a significant effect on
the behaviour of the algorithm. It is shown that only under extreme parameter settings
does the behaviour of Ant System and Max-Min Ant System differ from that of GBAS.
The thesis continues by investigating how inaccurate knowledge is used when it is the
heuristic that is at fault. This study reveals that Ant algorithms are not good at dealing
with this information, and if they do use a heuristic they must rely on it relating valid
guidance. An additional benefit of this study is that it shows heuristics may offer more
control over the exploration-exploitation trade-off than is afforded by other parameters.
The second point where knowledge enters the algorithm is through the local search.
The thesis looks at what happens to the performance of the Ant algorithms when a
local search is used and how this affects the parameters of the algorithm. It is shown
that the addition of a local search method does change the behaviour of the algorithm
and that the strength of the method has a strong influence on how the parameters are
The final study focuses on whether Ant algorithms are effective for driving a local
search method. The thesis demonstrates that these algorithms are not as effective as
some simpler fixed and variable neighbourhood search methods.|
|Description: ||Centre for Intelligent Systems and their Applications|
|Appears in Collections:||Informatics thesis and dissertation collection|
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