Revisiting Fast and Slow Thinking in Case-Based Reasoning

Srashti Kaurav; Devi Ganesan; Deepak P; Sutanu Chakraborti

doi:10.1007/978-3-030-86957-1_8

Revisiting Fast and Slow Thinking in Case-Based Reasoning

Srashti Kaurav, Devi Ganesan, Deepak P, Sutanu Chakraborti

School of Electronics, Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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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 language	English
Title of host publication	29th International Conference on Case-based Reasoning
Publisher	Springer
Number of pages	15
ISBN (Electronic)	978-3-030-86956-4
DOIs	https://doi.org/10.1007/978-3-030-86957-1_8
Publication status	Early online date - 21 Sept 2021
Event	29th International Conference on Case-based Reasoning - Salamanca, Spain Duration: 13 Sept 2021 → 16 Sept 2021 https://iccbr21.org/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
ISSN (Print)	0302-9743

Conference

Conference	29th International Conference on Case-based Reasoning
Abbreviated title	ICCBR 2021
Country/Territory	Spain
Period	13/09/2021 → 16/09/2021
Internet address	https://iccbr21.org/

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Revisiting Fast and Slow Thinking in Case-Based Reasoning
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Cite this

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title = "Revisiting Fast and Slow Thinking in Case-Based Reasoning",

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{\textquoteright}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.",

author = "Srashti Kaurav and Devi Ganesan and Deepak P and Sutanu Chakraborti",

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AU - Ganesan, Devi

AU - P, Deepak

AU - Chakraborti, Sutanu

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Y1 - 2021/9/21

N2 - 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.

AB - 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.

U2 - 10.1007/978-3-030-86957-1_8

DO - 10.1007/978-3-030-86957-1_8

M3 - Conference contribution

T3 - Lecture Notes in Computer Science

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PB - Springer

T2 - 29th International Conference on Case-based Reasoning

Y2 - 13 September 2021 through 16 September 2021

ER -

Revisiting Fast and Slow Thinking in Case-Based Reasoning

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