Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?

doi:10.1109/MCI.2018.2881645

Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?

2019-02-01

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DOI：10.1109/MCI.2018.2881645

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Evolutionary fuzzy systems are one of the greatest advances within the area of computational intelligence. They consist of evolutionary algorithms applied to the design of fuzzy systems. Thanks to this hybridization, superb abilities are provided to fuzzy modeling in many different data science scenarios. This contribution is intended to comprise a position paper developing a comprehensive analysis of the evolutionary fuzzy systems research field. To this end, the 4 W questions are posed and addressed with the aim of understanding the current context of this topic and its significance. Specifically, it will be pointed out why evolutionary fuzzy systems are important from an explainable point of view, when they began, what they are used for, and where the attention of researchers should be directed to in the near future in this area. They must play an important role for the emerging area of eXplainable Artificial Intelligence (XAI) learning from data.

Keywords:

RULE-BASED SYSTEMS

BIG DATA

CLASSIFICATION

METHODOLOGY

PREDICTION

MAPREDUCE

DISCOVERY

PROGRESS

INSIGHT

TRENDS

Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?

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