Modeling of Characteristics on Artificial Intelligence IQ Test: a Fuzzy Cognitive Map-Based Dynamic Scenario Analysis

Authors

Fangyao Liu, University of Nebraska at Omaha
Yayu Peng, University of Nebraska - Lincoln
Zhengxin Chen, University of Nebraska at Omaha
Yong Shi, University of Nebraska at Omaha

Document Type

Article

Publication Date

12-2019

Publication Title

International Journal of Computers Communications & Control

Volume

14

Issue

6

First Page

653

Last Page

669

Abstract

This research article uses a Fuzzy Cognitive Map (FCM) approach to improve an earlier proposed IQ test characteristics of Artificial Intelligence (AI) systems. The defuzzification process makes use of fuzzy logic and the triangular membership function along with linguistic term analyses. Each edge of the proposed FCM is assigned to a positive or negative influence type associated with a quantitative weight. All the weights are based on the defuzzified value in the defuzzification results. This research also leverages a dynamic scenario analysis to investigate the interrelationships between driver concepts and other concepts. Worst and best-case scenarios have been conducted on the correlation among concepts. We also use an inference simulation to examine the concepts importance order and the FCM convergence status. The analysis results not only examine the FCM complexity, but also draws insightful conclusions.

Comments

Copyright (c) 2019 Fangyao Liu, Yayu Peng, Zhengxin Chen, Yong Shi

Recommended Citation

Liu, Fangyao; Peng, Yayu; Chen, Zhengxin; and Shi, Yong, "Modeling of Characteristics on Artificial Intelligence IQ Test: a Fuzzy Cognitive Map-Based Dynamic Scenario Analysis" (2019). Information Systems and Quantitative Analysis Faculty Publications. 87.
https://digitalcommons.unomaha.edu/isqafacpub/87

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License