Thinking Fast and Slow: A CBR Perspective

Authors

  • Srashti Kaurav Indian Institute of Technology Madras
  • Devi Ganesan Indian Institute of Technology Madras
  • Deepak P Queen's University Belfast, United Kingdom, Indian Institute of Technology Madras
  • Sutanu Chakraborti Indian Institute of Technology Madras

DOI:

https://doi.org/10.32473/flairs.v34i1.128572

Keywords:

Case-based Reasoning, Fast Thinking, Slow Thinking, reasoning, cognition

Abstract

In a path-breaking work, Kahneman characterized human cognition as a result of two modes of operation, Fast Thinking and Slow Thinking. Fast thinking involves quick, intuitive decision making and slow thinking is deliberative conscious reasoning. In this paper, for the first time, we draw parallels between this dichotomous model of human cognition and decision making in Case-based Reasoning (CBR). We observe that fast thinking can be operationalized computationally as the fast decision making by a trained machine learning model, or a parsimonious CBR system that uses few attributes. On the other hand, a full-fledged CBR system may be seen as similar to the slow thinking process. We operationalize such computational models of fast and slow thinking and switching strategies, as Models 1 and 2. Further, we explore the adaptation process in CBR as a slow thinking manifestation, leading to Model 3. Through an extensive set of experiments on real-world datasets, we show that such realizations of fast and slow thinking are useful in practice, leading to improved accuracies in decision-making tasks.

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Published

2021-04-18

How to Cite

Kaurav, S., Ganesan, D., P, D., & Chakraborti, S. (2021). Thinking Fast and Slow: A CBR Perspective. The International FLAIRS Conference Proceedings, 34. https://doi.org/10.32473/flairs.v34i1.128572

Issue

Section

Main Track Proceedings