Quality-time-complexity universal intelligence measurement

International Journal of Crowd Science

article

Jing Liu¹  Zhiwen Pan¹  Jingce Xu¹  Bing Liang¹  Yiqiang Chen¹  Wen Ji² 

[1] Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology , Chinese Academy of Sciences, Beijing, China;Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology , Chinese Academy of Sciences, Beijing, China ...Show all authors

关键词: Turing test;    Agent–environment framework;    Algorithmic information theory;    Kolmogorov complexity;    Universal intelligence;   

DOI  :  10.1108/IJCS-04-2018-0007

学科分类：内科医学

来源: Emerald Publishing

【 摘 要 】

Purpose With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method. Design/methodology/approach This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents. Findings By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment. Originality/value This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.

【 授权许可】

CC BY