quantum Case-Based Reasoning (qCBR)
Abstract
Case-Based Reasoning (CBR) is an artificial intelligence approach to problem-solving with a good record of success. This article proposes using Quantum Computing to improve some of the key processes of CBR, such that a Quantum Case-Based Reasoning (qCBR) paradigm can be defined. The focus is set on designing and implementing a qCBR based on the variational principle that improves its classical counterpart in terms of average accuracy, scalability and tolerance to overlapping. A comparative study of the proposed qCBR with a classic CBR is performed for the case of the Social Workers' Problem as a sample of a combinatorial optimization problem with overlapping. The algorithm's quantum feasibility is modelled with docplex and tested on IBMQ computers, and experimented on the Qibo framework.
Cite
@article{arxiv.2104.00409,
title = {quantum Case-Based Reasoning (qCBR)},
author = {Parfait Atchade-Adelomou and Daniel Casado-Fauli and Elisabet Golobardes-Ribe and Xavier Vilasis-Cardona},
journal= {arXiv preprint arXiv:2104.00409},
year = {2022}
}
Comments
17 pages, 19 figures, 9 tables