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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Memetic Computing In Selected Agent-Based Evolutionary Systems |
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Authors: |
Aleksander Byrski, Marek Kisiel-Dorohinicki |
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Published in:
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(2014).ECMS 2014 Proceedings edited
by: Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani
European Council for Modeling and Simulation. doi:10.7148/2014 ISBN:
978-0-9564944-8-1 28th
European Conference on Modelling and Simulation, Brescia,
Italy, May 27th – 30th,
2014 |
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Citation
format: |
Aleksander
Byrski, Marek Kisiel-Dorohinicki (2014). Memetic
Computing In Selected Agent-Based Evolutionary Systems, ECMS 2014 Proceedings
edited by: Flaminio Squazzoni, Fabio Baronio, Claudia Archetti, Marco Castellani European Council for Modeling and
Simulation. doi:10.7148/2014-0495 |
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DOI: |
http://dx.doi.org/10.7148/2014-0495 |
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Abstract: |
In the paper an application
of selected agent-based evolu- tionary computing models, such as flock-based
multi agent sys- tem (FLOCK) and evolutionary multi-agent system (EMAS), to
the problem of continuous optimisation is presented. It turns out, that hybridizing
of agent-based paradigm with evolution- ary computation brings a new quality
to the meta-heuristic field, easily enhancing static individuals with
possibilities of perception and interaction with other agents. The
examination of selected benchmarks leads to the observation regarding the
overall efficiency of the systems in comparison to the standard genetic
algorithm (as defined by Michalewicz) and memetic versions of all the systems.
The experiments confirm that the efficiency is dependent on the problem, however,
the observed number of fitness function calls makes EMAS dominate over its competitors.
This feature makes EMAS a promising solution for the problems with complex
fitness functions, (such as inverse problems). |
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