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Open AccessArticle

Logic-Based Technologies for Intelligent Systems: State of the Art and Perspectives

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Alma AI—Alma Mater Research Institute for Human-Centered Artificial Intelligence, Alma Mater Studiorum–Università di Bologna, 40121 Bologna, Italy
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Dipartimento di Informatica–Scienza e Ingegneria (DISI), Alma Mater Studiorum–Università di Bologna, 47522 Cesena, Italy
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Dipartimento di Informatica–Scienza e Ingegneria (DISI), Alma Mater Studiorum–Università di Bologna, 40136 Bologna, Italy
*
Author to whom correspondence should be addressed.
Information 2020, 11(3), 167; https://doi.org/10.3390/info11030167
Received: 25 February 2020 / Revised: 16 March 2020 / Accepted: 18 March 2020 / Published: 22 March 2020
(This article belongs to the Special Issue 10th Anniversary of Information—Emerging Research Challenges)
Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future. View Full-Text
Keywords: symbolic AI; logic-based technologies; intelligent systems symbolic AI; logic-based technologies; intelligent systems
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Calegari, R.; Ciatto, G.; Denti, E.; Omicini, A. Logic-Based Technologies for Intelligent Systems: State of the Art and Perspectives. Information 2020, 11, 167.

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