Using Cultural Algorithms with Common Value Auctions to Provide Sustainability in Complex Dynamic Environments

被引:0
|
作者
Al-Tirawi, Anas [1 ]
Reynolds, Robert G. [1 ,2 ]
机构
[1] Wayne State Univ, Dept Comp Sci, Detroit, MI 48202 USA
[2] Univ Michigan, Museum Anthropol Archaeol, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
cultural algorithms; common value auctions; wisdom of the crowds; evolutionary algorithms; social networks; sustainable learning; dynamic environments;
D O I
10.1109/AIKE48582.2020.00042
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In Computation intelligence algorithm performance is crucial especially when the complexity of the system increases and becomes chaotic (unpredictable). In Cultural Systems many algorithms are able to predict the system performance as the complexity is linear, or non-linear. However, when it is chaotic the prediction quality decreases dramatically. In this paper, we are show that Common Value Auctions are able to distribute sufficient information through the system in order to sustain the prediction rate even on the edge of chaos. This sustainability is expressed here in terms of increased resilience and robustness. Systems that rely on wisdom of the crowd based approaches are shown not to do as well when environmental change goes from linear to non-linear, and finally to chaotic.
引用
收藏
页码:84 / 91
页数:8
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