Exploiting non-dominance in multi agent systems: An artificial immune algorithm for distributed and complex Problem solving environments

Efatmaneshnik, Mahmoud and Reidsema, Carl (2008). Exploiting non-dominance in multi agent systems: An artificial immune algorithm for distributed and complex Problem solving environments. In: Suzanne Sadedin, Greg Paperin and Tania Leishman, Proceedings of the 12th Asia Pacific Symposium on Intelligent and Evolutionary Systems. 12th Asia Pacific Symposium on Intelligent and Evolutionary Systems, Melbourne, Australia, (106-115). 8-9 December 2008.

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Author Efatmaneshnik, Mahmoud
Reidsema, Carl
Title of paper Exploiting non-dominance in multi agent systems: An artificial immune algorithm for distributed and complex Problem solving environments
Conference name 12th Asia Pacific Symposium on Intelligent and Evolutionary Systems
Conference location Melbourne, Australia
Conference dates 8-9 December 2008
Proceedings title Proceedings of the 12th Asia Pacific Symposium on Intelligent and Evolutionary Systems
Place of Publication Melbourne, Australia
Publisher Monash University
Publication Year 2008
Sub-type Fully published paper
ISBN 9780646506715
Editor Suzanne Sadedin
Greg Paperin
Tania Leishman
Start page 106
End page 115
Total pages 10
Language eng
Abstract/Summary An ideal Multi Agent System is flat and has no dominant hierarchy. Multi agent computational and problem solving environments have been advocated for their ability to deliver overall solutions that are innovative and creative. There is however a significant threat to the coherence of Multi Agent Systems; chaos. This paper poses a new vision to the control and immunisation of the Multi Agent Systems against chaos. Employing a complexity measure of the problem and its lower and upper bounds, and monitoring the complexity of the problem solving agents’ interactions, we propose the holistic control of the Multi Agent Systems that leads to immunisation of the system against chaos. The control however is not central and appears in the form of the agents’ common knowledge and determines their tendency to proactively communicate.
Keyword Multi agent systems
Immunity
Chaos
Complexity measure
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Non-UQ

 
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Created: Thu, 27 Oct 2011, 15:03:52 EST by Viviane Victoria Crosthwaite on behalf of Faculty Of Engineering, Architecture & Info Tech