DocumentCode :
2104744
Title :
Dependable Risk-Aware Efficiency Improvement for Self-Organizing Emergent Systems
Author :
Hudson, Jonathan ; Denzinger, Jörg ; Kasinger, Holger ; Bauer, Bernhard
Author_Institution :
Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB, Canada
fYear :
2011
fDate :
3-7 Oct. 2011
Firstpage :
11
Lastpage :
20
Abstract :
An efficiency improvement advisor agent acts as a consultation service for a self-organizing multi-agent system that improves operational efficiency. It identifies recurrent tasks in past problems that allow the creation of so-called exception rules for individual agents to limit future inefficient behavior. There exists the danger that introduced rules could possibly infringe on the flexibility and therefore reliability of the system. In this paper, we present a dependable risk-aware efficiency improvement advisor that uses Monte Carlo simulation techniques in strategic analysis assessing the long-term potential and risks of prospective rules. Our experimental evaluation, for the domain of dynamic pickup and delivery problems, shows that the result is a minimal, yet effective, set of risk-averse exception rules. These rules can be provided to individual agents to reliably achieve an overall long-term improvement in efficiency while maintaining flexibility.
Keywords :
Monte Carlo methods; multi-agent systems; risk management; Monte Carlo simulation techniques; consultation service; dependable risk aware efficiency improvement advisor; efficiency improvement advisor agent; exception rules; prospective rules; risk averse exception rules; self organizing multiagent system; strategic analysis; Control systems; Data mining; History; Monte Carlo methods; Multiagent systems; Reliability; Stochastic processes; control; dependability; risk management; self-organization; software architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Self-Adaptive and Self-Organizing Systems (SASO), 2011 Fifth IEEE International Conference on
Conference_Location :
Ann Arbor, MI
ISSN :
1949-3673
Print_ISBN :
978-1-4577-1614-0
Electronic_ISBN :
1949-3673
Type :
conf
DOI :
10.1109/SASO.2011.12
Filename :
6063483
Link To Document :
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