DocumentCode :
3399826
Title :
Using cultural algorithms to evolve strategies for recessionary markets
Author :
Ostrowski, David A. ; Reynolds, Robert G.
Author_Institution :
Res. & Adv. Eng., Ford Motor Co., Dearborn, MI, USA
Volume :
2
fYear :
2004
fDate :
19-23 June 2004
Firstpage :
1780
Abstract :
Cultural algorithms are computational self-adaptive models consisting of a population and a belief space. Two cultural algorithms are applied, with one supporting white box testing and the second black box testing. The two populations communicate with each other by means of a shared belief space. This is applied to the calibration of a multi-agent system by allowing for evolution of near optimal parameters. The cultural approach is employed to abstract coefficients of pricing strategies that are applied to a complex model of durable goods. This model simulates consumer behaviors as applied in the context of economic recession.
Keywords :
belief networks; evolutionary computation; large-scale systems; multi-agent systems; pricing; self-adjusting systems; simulation; software engineering; abstract coefficients; black box testing; computational self-adaptive models; consumer behaviors; cultural algorithms; durable goods; economic recession; multiagent system; near optimal parameters; pricing strategies; recessionary markets; shared belief space; white box testing; Context modeling; Cultural differences; Evolutionary computation; Fault diagnosis; Global communication; Logic testing; Multiagent systems; Programming profession; Software design; Software testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN :
0-7803-8515-2
Type :
conf
DOI :
10.1109/CEC.2004.1331111
Filename :
1331111
Link To Document :
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