Using software engineering knowledge to drive genetic program design using cultural algorithms - Exploiting the synergy of software engineering knowledge in evolutionary design

被引:0
|
作者
Ostrowski, DA [1 ]
Reynolds, RG [1 ]
机构
[1] Ford Motor Co, Sci Res Labs, Dearborn, MI 48121 USA
关键词
genetic programming; cultural algorithms; hybrid genetic programming; environments; agent-based Modeling; OEM strategy evolution; black box testing; white box testing;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we use Cultural Algorithms as a framework in which to embed a white and black box testing strategy for designing and testing large-scale GP programs. ne model consists of two populations, one supports white box testing of a genetic programming system and the other supports black box testing. The two populations communicate by sending information to a shared belief space. This allows a potential synergy between the two activities. Next, we exploit this synergy in order to evolve an OEM pricing strategy in a complex agent-based market environment. The new pricing strategy generated over $2 million dollars in revenue during the assessment period and outperformed the previous optimal strategy.
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页码:63 / 80
页数:18
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