Revisiting Fast and Slow Thinking in Case-Based Reasoning

Srashti Kaurav, Devi Ganesan, Deepak P, Sutanu Chakraborti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A dichotomous Case-Based Reasoning (CBR) model is one in which two kinds of reasoning mechanisms are employed for realizing fast and slow problem-solving as demanded by the nature of the incoming query. This is inspired by Daniel Kahneman’s seminal work on the two modes of thinking observed in humans. In this paper, we present the following three directions of refinement for a dichotomous CBR model: selection of attributes for a fast thinking model based on parsimonious CBR, switching from fast to slow thinking based on constraints derived from domain knowledge and arriving at a complexity measure for evaluating dichotomous models. For all the three improvements identified, we discuss the results on real-world data sets and empirically analyse the effectiveness of the same.
Original languageEnglish
Title of host publication29th International Conference on Case-based Reasoning
Number of pages15
Publication statusAccepted - 10 Jun 2021
Event29th International Conference on Case-based Reasoning - Salamanca, Spain
Duration: 13 Sep 202116 Sep 2021
https://iccbr21.org/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
ISSN (Print)0302-9743

Conference

Conference29th International Conference on Case-based Reasoning
Abbreviated titleICCBR 2021
CountrySpain
Period13/09/202116/09/2021
Internet address

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