A Mathematical Review on Machine Intelligence Quotient (MIQ) Theory in Real-World Applications

Subject Areas : International Journal of Mathematical Modelling & Computations

Aref Safari ¹ (Department of Computer Engineering, Rasht Branch, Islamic Azad University, Rasht, Iran)

Received: 2020-12-23 Accepted : 2021-02-09 Published : 2021-03-01

Keywords: fuzzy logic, HLMI, MIQ, Computing with Words,

Abstract :

Complex systems and information flow such as command, control, communication, computer intelligence, inference, and expert systems exhibit an increasing dependence on the system's nature and information flow. For this reason, it is both the flow exchange of information in the system and the emergent information properties of the system, which are central to the definition, design and analysis of such systems. Besides, the achievement of human-level machine intelligence has long been one of the principal objectives of Artificial Intelligence (AI). Machine intelligence methods have gained many orders of magnitude in computational capability in the last decade, especially in cognitive science and cognitive informatics. This research discussed the difference between Human IQ and Machine Intelligence Quotient (MIQ). Also, we show that MIQ is an abstract intelligence and soft concept of artificial intelligence. Finally, we conclude that the fuzzy sets can better represent MIQ instead of probabilistic and numerical methods.