Book contents
- The Cambridge Handbook of Computational Cognitive Sciences
- Cambridge Handbooks in Psychology
- The Cambridge Handbook of Computational Cognitive Sciences
- Copyright page
- Contents
- Preface
- Contributors
- Part I Introduction
- Part II Cognitive Modeling Paradigms
- Part III Computational Modeling of Basic Cognitive Functionalities
- 11 Computational Models of Categorization
- 12 Computational Cognitive Neuroscience Models of Categorization
- 13 Models of Inductive Reasoning
- 14 Analogy and Similarity
- 15 Mental Models and Algorithms of Deduction
- 16 Computational Models of Decision Making
- 17 Computational Models of Skill Acquisition
- 18 Computational Models of Episodic Memory
- 19 Computational Neuroscience Models of Working Memory
- 20 Neurocomputational Models of Cognitive Control
- 21 Computational Models of Animal and Human Associative Learning
- 22 Computational Cognitive Models of Reinforcement Learning
- Part IV Computational Modeling in Various Cognitive Fields
- Part V General Discussion
- Index
- References
13 - Models of Inductive Reasoning
from Part III - Computational Modeling of Basic Cognitive Functionalities
Published online by Cambridge University Press: 21 April 2023
Edited by
Book contents
- The Cambridge Handbook of Computational Cognitive Sciences
- Cambridge Handbooks in Psychology
- The Cambridge Handbook of Computational Cognitive Sciences
- Copyright page
- Contents
- Preface
- Contributors
- Part I Introduction
- Part II Cognitive Modeling Paradigms
- Part III Computational Modeling of Basic Cognitive Functionalities
- 11 Computational Models of Categorization
- 12 Computational Cognitive Neuroscience Models of Categorization
- 13 Models of Inductive Reasoning
- 14 Analogy and Similarity
- 15 Mental Models and Algorithms of Deduction
- 16 Computational Models of Decision Making
- 17 Computational Models of Skill Acquisition
- 18 Computational Models of Episodic Memory
- 19 Computational Neuroscience Models of Working Memory
- 20 Neurocomputational Models of Cognitive Control
- 21 Computational Models of Animal and Human Associative Learning
- 22 Computational Cognitive Models of Reinforcement Learning
- Part IV Computational Modeling in Various Cognitive Fields
- Part V General Discussion
- Index
- References
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.
- Type
- Chapter
- Information
- The Cambridge Handbook of Computational Cognitive Sciences , pp. 426 - 450Publisher: Cambridge University PressPrint publication year: 2023
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