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quantum Case-Based Reasoning

2021-04-01 11:34:22
Parfait Atchade-Adelomou, Daniel Casado-Fauli, Elisabet Golobardes-Ribe, Xavier Vilasis-Cardona

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 defining so a Quantum Case-Based Reasoning (qCBR) paradigm. 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.

Abstract (translated)

URL

https://arxiv.org/abs/2104.00409

PDF

https://arxiv.org/pdf/2104.00409.pdf


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