Pervasiveness of ICT resources along with the promise of ubiquitous intelligence is pushing hard both our demand and our fears of AI: demand mandates for the ability to inject (micro) intelligence ubiquitously, fears compel the behaviour of intelligent systems to be observable, explainable, and accountable. Whereas the first wave of the new “AI Era” was mostly heralded by sub-symbolic approaches, features like explainability are better provided by symbolic techniques. In this paper we focus on logic-based approaches, and discuss their potential in pervasive scenarios like the IoT and open (M)MAS along with our latest results in the field.
CITATION STYLE
Omicini, A., & Calegari, R. (2019). Injecting (Micro)Intelligence in the IoT: Logic-Based Approaches for (M)MAS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11422 LNAI, pp. 21–35). Springer Verlag. https://doi.org/10.1007/978-3-030-20937-7_2
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