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Reflective Reasoning in a Case-Based Reasoning Agent

Authors: Miquel Sànchez-Marrè; Ulises Cortés; Javier Béjar; Ignasi R.-Roda; Manel Poch;

Reflective Reasoning in a Case-Based Reasoning Agent

Abstract

As a Case-Based Reasoning agent (CBR) evolves over time, and solves new problems based on previous experiences, there are some pitfalls that can appear in the problem-solving task. When those troubles arise, is the time to start some reflective reasoning tasks to overcome those problems and to improve the CBR performance. Our proposal is to extend the basic reasoning and learning cycle with some new added reflective tasks such as forgetting cases, learning new cases, updating the case library organisation or re-exploring the case library, and including other strategies such as building meta-cases.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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