Game Theoretic Approach for Applying Artificial Intelligence in the Credit Industry

被引:0
|
作者
Romanyuk, Kirill [1 ]
机构
[1] Natl Res Univ, Higher Sch Econ, Dept Finance, St Petersburg, Russia
关键词
Artificial Intelligence; Machine Learning; Game Theory; Deep Learning; Credit Industry; GO;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The law of accelerating returns can be viewed as a concept that describes acceleration of technological progress. The idea is that tools are used for developing more advanced tools that are applied for creating even more advanced tools etc. A similar idea has been implemented in algorithms for advancing artificial intelligence. In this paper, the results of applying these algorithms in games are discussed. Nevertheless, real life tasks seem more complicated. The game theoretic approach can be applied for transition from theoretical and unrealistic games to more complex and practical tasks. Applications of the game theoretic approach to advance artificial intelligence in solving tasks in the credit industry are proposed.
引用
收藏
页码:1 / 6
页数:6
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