Reducing Reliance on Domain Knowledge in Case-Based Reasoning - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Reducing Reliance on Domain Knowledge in Case-Based Reasoning

Résumé

Case-based reasoning is an intuitive approach to problem-solving in artificial intelligence that involves reusing existing experience, including solutions to problems or mechanisms to derive them. However, current Case-based reasoning systems suffer from a lack of generality due to their heavy reliance on domain-specific knowledge, and they often struggle with the adaptation process, which is driven by the application domain. In addition, these systems often perform poorly as they treat each step of the Case-based reasoning methodology separately and independently. To address these limitations, this work proposes a domain-independent Case-based reasoning framework that integrates each step of the reasoning process to support other stages of the process. The framework is evaluated in an experimental setting on a sober consumption energy system in buildings, demonstrating its effectiveness.
Fichier non déposé

Dates et versions

hal-04382417 , version 1 (09-01-2024)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Fateh Boulmaiz, Patrick Reignier, Stephane Ploix. Reducing Reliance on Domain Knowledge in Case-Based Reasoning. IEA/AIE 2023: Advances and Trends in Artificial Intelligence. Theory and Applications, Jul 2023, Shanghai, China. pp.3-13, ⟨10.1007/978-3-031-36819-6_1⟩. ⟨hal-04382417⟩
6 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More