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Towards Addressing Problem-Distribution Drift with Case Discovery

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Case-Based Reasoning Research and Development (ICCBR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14141))

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Abstract

Case-based reasoning (CBR) is a problem-solving and learning methodology that applies records of past experiences, captured as cases, to solve new problems. The performance of CBR depends on retrieving cases relevant to each new problem that the reasoner encounters. In real-world applications, the distribution of problems can change over time, which can cause an issue for the competence and efficiency of CBR systems. This paper proposes addressing this issue through predictive case discovery, which involves predicting cases expected to be useful for future problems to acquire them in advance. It presents an overview of case discovery for problem-distribution drift, including the challenges involved, proposed strategies, and future research directions. It illustrates with a case study evaluating a clustering-based case discovery strategy in a path planning domain across four scenarios: no drift, non-cyclical drift, cyclical drift, and drift from obsolescence.

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Notes

  1. 1.

    https://github.com/schackbrian2012/ICCBR-2023.

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Acknowledgments

This work was funded in part by the Department of the Navy, Office of Naval Research (Award N00014-19-1-2655).

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Authors and Affiliations

  1. Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA

    David Leake & Brian Schack

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  1. David Leake
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  2. Brian Schack
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Correspondence to David Leake .

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Editors and Affiliations

  1. Robert Gordon University, Aberdeen, UK

    Stewart Massie

  2. Indian Institute of Technology Madras, Chennai, Tamil Nadu, India

    Sutanu Chakraborti

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Leake, D., Schack, B. (2023). Towards Addressing Problem-Distribution Drift with Case Discovery. In: Massie, S., Chakraborti, S. (eds) Case-Based Reasoning Research and Development. ICCBR 2023. Lecture Notes in Computer Science(), vol 14141. Springer, Cham. https://doi.org/10.1007/978-3-031-40177-0_16

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  • DOI: https://doi.org/10.1007/978-3-031-40177-0_16

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