Moret-Bonillo, VicenteMosqueira-Rey, EduardoMagaz-Romero, SamuelGómez Tato, AndrésMusso, Daniele2025-02-112025-02-112021-11Moret-Bonillo, V., Mosqueira-Rey, E., Magaz-Romero, S.. Gómez-Tato, A., Musso, D. (2021). Quantum Rule-Based Systems: Managing Uncertain Information with Quantum Computing [poster]. European Quantum Technologies Conference 2021 (EQTC2021).http://hdl.handle.net/2183/41151Poster presented in EQTC 2021 - 2nd European Quantum Technologies Virtual Conference that took place from 29th November – 2nd December 2021 in a “virtual” format conference.[Abstract]: This poster was presented in EQTC 2021; expressing the early ideas behind the methodology of Quantum Rule-Based Systems (QRBS). Rule-based systems (RBSs) are systems that apply human-made rules to store, sort and manipulate data in an attempt to mimic human intelligence. These systems are considered the simplest form of Artificial Intelligence (AI), yet they can be found applied in many different environments. A problem that may come up when working with systems of this kind is uncertainty. Uncertainty may arise on these models as a consequence of the propagation of imprecision through the inferential network. This problem has been treated with different classical models, such as Bayesian Networks or the Certainty Factors Method. However, none of them provide a “definitive solution”. Therefore, we propose a new approach to modelling said uncertainty by the means of Quantum Computing, and its intrinsically probabilistic nature. This new approach will allow to develop what we call Quantum Rule-Based Systems (QRBSs).engTodos os dereitos reservados. Todos los derechos reservados. All rights reserved.Quantum Rule-Based SystemsQuantum ComputingUncertaintyconference outputopen access