The case-based reasoning community is successfully pursuing multiple approaches for applying deep learning methods to advance case-based reasoning. This “Challenges and Promises” paper argues for a complementary endeavor: pursuing ways that the case-based reasoning methodology can advance deep learning. Starting from challenges in deep learning and proposed neural-symbolic integrations based on specific technologies, it proposes studying how CBR ideas can inform choices of components for a new reasoning pipeline.
CITATION STYLE
Leake, D., & Crandall, D. (2020). On Bringing Case-Based Reasoning Methodology to Deep Learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12311 LNAI, pp. 343–348). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58342-2_22
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