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Related Experiment Video

Updated: Jun 12, 2025

Designing and Implementing Nervous System Simulations on LEGO Robots

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Published on: May 25, 2013

Learning by thinking in natural and artificial minds.

Tania Lombrozo¹

¹Department of Psychology, Princeton University, Princeton, NJ 08540, USA.

Trends in Cognitive Sciences

|September 19, 2024

Summary

This summary is machine-generated.

Learning by thinking (LbT) allows minds, both human and artificial, to generate new knowledge internally. This process is crucial for constructing knowledge representations on demand in uncertain environments.

Keywords:

analogical reasoning artificial intelligence learning self-explanation simulation thought experiments

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Perspectives on Neuroscience

Perspectives on Neuroscience

Published on: July 31, 2007

Area of Science:

Cognitive Science
Artificial Intelligence
Neuroscience

Background:

Traditional learning models focus on external observations.
Mental processes like reasoning and simulation also drive learning.
Artificial intelligence (AI) is demonstrating 'learning by thinking' (LbT) capabilities.

Purpose of the Study:

To resolve the paradox of how internal mental processes generate new knowledge.
To highlight the role of 'learning by thinking' in natural and artificial minds.
To explain how minds construct knowledge representations on demand.

Main Methods:

Conceptual analysis of internal knowledge generation.
Review of recent AI advancements in self-correction and reasoning.
Exploration of 'learning by thinking' mechanisms.

Main Results:

Learning can occur through internal mental processes, not just external input.
Artificial minds exhibit 'learning by thinking', mirroring human cognitive abilities.
LbT enables the on-demand construction of knowledge representations.

Conclusions:

'Learning by thinking' is a fundamental mechanism for knowledge acquisition in both biological and artificial systems.
This internal learning process is essential for navigating complex and uncertain environments.
Understanding LbT is key to developing more sophisticated AI and understanding human cognition.