Automated Mechanism Design with Co-Evolutionary Hierarchical Genetic Programming Techniques

被引:0
作者
Doucette, John A. [1 ]
Abramson, Darren [1 ]
机构
[1] Univ Waterloo, David R Cheriton Sch Comp Sci, Waterloo, ON N2L 3G1, Canada
来源
PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE | 2012年
关键词
Coevolution; Automated Mechanism Design; SOCIAL-WELFARE; FAIRNESS; GAME;
D O I
10.1145/2330163.2330293
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We present a novel form of automated game theoretic mechanism design in which mechanisms and players co-evolve. We also model the memetic propagation of strategies through a population of players, and argue that this process represents a more accurate depiction of human behavior than conventional economic models. The resulting model is evaluated by evolving mechanisms for the ultimatum game, and replicates the results of empirical studies of human economic behaviors, as well as demonstrating the ability to evaluate competing hypothesises for the creation of economic incentives.
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页码:935 / 942
页数:8
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