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QL-CBR Hybrid Approach for Adapting Context-Aware Services

Somia Belaidouni1,2, Moeiz Miraoui3,4,*, Chakib Tadj1

1 Ecole de Technologie Supérieure, Montréal, QCH3C1K3, Canada
2 Faculty of Exact and Applied Sciences, University of Oran 1, Oran, 31000, Algeria
3 Higher Institute of Sciences and Technologies, University of Gafsa, Gafsa, 2100, Tunisia
4 AL-Lith Computer College, Umm Al-Qura University, Al-Lith, 28434, Saudi Arabia

* Corresponding Author: Moeiz Miraoui. Email: email

Computer Systems Science and Engineering 2022, 43(3), 1085-1098.


A context-aware service in a smart environment aims to supply services according to user situational information, which changes dynamically. Most existing context-aware systems provide context-aware services based on supervised algorithms. Reinforcement algorithms are another type of machine-learning algorithm that have been shown to be useful in dynamic environments through trial-and-error interactions. They also have the ability to build excellent self-adaptive systems. In this study, we aim to incorporate reinforcement algorithms (Q-learning) into a context-aware system to provide relevant services based on a user’s dynamic context. To accelerate the convergence of reinforcement learning (RL) algorithms and provide the correct services in real situations, we propose a combination of the Q-learning and case-based reasoning (CBR) algorithms. We then analyze how the incorporation of CBR enables Q-learning to become more efficient and adapt to changing environments by continuously producing suitable services. Simulation results demonstrate the effectiveness of the proposed approach compared to the traditional CBR approach.


Cite This Article

APA Style
Belaidouni, S., Miraoui, M., Tadj, C. (2022). QL-CBR hybrid approach for adapting context-aware services. Computer Systems Science and Engineering, 43(3), 1085-1098.
Vancouver Style
Belaidouni S, Miraoui M, Tadj C. QL-CBR hybrid approach for adapting context-aware services. Comput Syst Sci Eng. 2022;43(3):1085-1098
IEEE Style
S. Belaidouni, M. Miraoui, and C. Tadj "QL-CBR Hybrid Approach for Adapting Context-Aware Services," Comput. Syst. Sci. Eng., vol. 43, no. 3, pp. 1085-1098. 2022.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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