Role of Fuzzy Sets on Artificial Intelligence Methods: A literature Review
محورهای موضوعی : Transactions on Fuzzy Sets and Systems
Cengiz Kahraman
1
,
Sezi Onar
2
,
Basar Oztaysi
3
,
Selcuk Cebi
4
1 - Department of Industrial Engineering, IStanbul Technical University, Istanbul, Turkey.
2 - Department of Industrial Engineering, IStanbul Technical University, Istanbul, Turkey.
3 - Department of Industrial Engineering, IStanbul Technical University Istanbul, Turkey.
4 - Department of Industrial Engineering, Yildiz Technical University, Istanbul, Turkey.
کلید واژه: Artificial intelligence, Fuzzy sets, Automated reasoning, Autonomous agents, Machine learning, Deep learning, Information reasoning, Neural networks,
چکیده مقاله :
Machines can model and improve the human minds capabilities through artificial intelligence. One of the most popular tools of artificial intelligence is fuzzy sets, which can capture and model the vagueness and impreciseness in human thoughts. This paper, first of all, introduces the recent extensions of ordinary fuzzy sets and then presents a literature review on the integration of fuzzy sets with other artificial intelligence techniques such as automated reasoning, autonomous agents, multi-agent systems, machine learning, case-based reasoning, deep learning, information reasoning, information representation, natural language processing, symbolic reasoning, and neural networks. Graphical illustrations of literature review results are presented for each of these integrated artificial intelligence techniques. The results of a patent search on fuzzy artificial intelligence are also given.
Machines can model and improve the human minds capabilities through artificial intelligence. One of the most popular tools of artificial intelligence is fuzzy sets, which can capture and model the vagueness and impreciseness in human thoughts. This paper, first of all, introduces the recent extensions of ordinary fuzzy sets and then presents a literature review on the integration of fuzzy sets with other artificial intelligence techniques such as automated reasoning, autonomous agents, multi-agent systems, machine learning, case-based reasoning, deep learning, information reasoning, information representation, natural language processing, symbolic reasoning, and neural networks. Graphical illustrations of literature review results are presented for each of these integrated artificial intelligence techniques. The results of a patent search on fuzzy artificial intelligence are also given.
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