This Specialty Section is at the forefront of disseminating and communicating fuzzy logic scientific knowledge and impactful discoveries to academia, industry and the public worldwide. The recent increases in computing power, coupled with rapid growth in the availability and quantity of data have resulted in a resurgence of interest in the theory and applications of Artificial intelligence (AI). However, for AI to be confidently rolled out by industries and governments, there is a need for greater transparency in explaining the AI decision making process to users to generate "White/Transparent Box" models, also termed Explainable AI (XAI). Fuzzy logic attempts to mimic human thinking, playing an important role in modelling and representing imprecise and uncertain linguistic human concepts. In addition, fuzzy logic provides tools to model a given behavior in a human-readable form. Thus, fuzzy logic theory and applications can play an important role to contribute to development of XAI models which can deployed in various domains to allow AI potential to be fully realized while allowing full user trust and transparency behind given model decisions/predictions.
This Specialty Section provides a forum for fuzzy logic research spanning all areas of fuzzy sets and systems theory, hybrid fuzzy systems to real world fuzzy logic applications which impact people lives all over the world. Given the relevance of fuzzy logic concepts to social science, linguistics and psychology, we encourage research looking at inter-disciplinary research including intersections with the fields of computer science, social science, linguistics, psychology, economics, health, etc. Some relevant topics include but are not limited to: fuzzy preference modelling, computing with words, fuzzy decision making, aggregation operators, group decision making, consensus, fuzzy approaches in social networks, fuzzy approaches in IR and recommender systems, fuzzy approaches in Internet of Things, fuzzy approaches in web intelligence, fuzzy approaches in big data, fuzzy approaches in web intelligence and fuzzy systems and applications.
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Fuzzy Systems welcomes submissions of the following article types: Code, Core Concept, Correction, Data Report, General Commentary, Hypothesis and Theory, Methods, Mini Review, New Discovery, Opinion, Original Research, Perspective, Review, Specialty Grand Challenge and Technology Report.
All manuscripts must be submitted directly to the section Fuzzy Systems, where they are peer-reviewed by the Associate and Review Editors of the specialty section.
Articles published in the section Fuzzy Systems will benefit from the Frontiers impact and tiering system after online publication. Authors of published original research with the highest impact, as judged democratically by the readers, will be invited by the Chief Editor to write a Frontiers Focused Review - a tier-climbing article. This is referred to as "democratic tiering". The author selection is based on article impact analytics of original research published in all Frontiers specialty journals and sections. Focused Reviews are centered on the original discovery, place it into a broader context, and aim to address the wider community across all of Artificial Intelligence.
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