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Quality-time-complexity universal intelligence measurement

机译：质量-时间-复杂度通用智能测量

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Purpose With development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more and more autonomous and smart. Therefore, there is a growing demand to develop 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. Practical implications In a crowd network, a number of intelligent agents are able to collaborate with each other to finish a certain kind of sophisticated tasks. The proposed approach can be used to allocate the tasks to the agents within a crowd ...
机译：目的随着机器学习技术的发展，诸如人群网络之类的人工智能系统变得越来越自治和智能。因此，对开发通用智能测量的需求不断增长，以便可以评估人工智能系统的智能。本文旨在提出一种更加形式化和准确的机器智能测量方法。设计/方法/方法本文提出了一种质量-时间-复杂度通用智能度量方法，用于度量代理的智能。结果通过观察代理与环境之间的交互过程，我们抽象出了用于智能度量的三个主要因素，即质量，时间和环境复杂性。实际意义在人群网络中，许多智能代理能够相互协作以完成某种复杂的任务。所提出的方法可用于将任务分配给人群中的代理...

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