Models of Inductive Reasoning

doi:10.1017/9781108755610.017

13 - Models of Inductive Reasoning

from Part III - Computational Modeling of Basic Cognitive Functionalities

Published online by Cambridge University Press: 21 April 2023

Brett K. Hayes

Edited by

Ron Sun

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Ron Sun: Affiliation:
Rensselaer Polytechnic Institute, New York

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Summary

Inductive reasoning involves using existing knowledge to make predictions about novel cases. This chapter reviews and evaluates computational models of this fundamental aspect of cognition, with a focus on work involving property induction. The review includes early induction models such as similarity coverage, and the feature-based induction model, as well as a detailed coverage of more recent Bayesian and connectionist approaches. Each model is examined against benchmark empirical phenomena. Model limitations are also identified. The chapter highlights the major advances that have been made in our understanding of the mechanisms that drive induction, as well as identifying challenges for future modeling. These include accounting for individual and developmental differences and applying induction models to explain other forms of reasoning.

Keywords

reasoning induction categorization Bayesian modeling similarity generalization

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Type: Chapter
Information: The Cambridge Handbook of Computational Cognitive Sciences , pp. 426 - 450
DOI: https://doi.org/10.1017/9781108755610.017 [Opens in a new window]
Publisher: Cambridge University Press
Print publication year: 2023

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