Abstract
Canonical cases of learning involve novel observations external to the mind, but learning can also occur through mental processes such as explaining to oneself, mental simulation, analogical comparison, and reasoning. Recent advances in artificial intelligence (AI) reveal that such learning is not restricted to human minds: artificial minds can also self-correct and arrive at new conclusions by engaging in processes of 'learning by thinking' (LbT). How can elements already in the mind generate new knowledge? This article aims to resolve this paradox, and in so doing highlights an important feature of natural and artificial minds – to navigate uncertain environments with variable goals, minds with limited resources must construct knowledge representations 'on demand'. LbT supports this construction.
Original language | English (US) |
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Pages (from-to) | 1011-1022 |
Number of pages | 12 |
Journal | Trends in Cognitive Sciences |
Volume | 28 |
Issue number | 11 |
DOIs | |
State | Published - Nov 2024 |
All Science Journal Classification (ASJC) codes
- Neuropsychology and Physiological Psychology
- Experimental and Cognitive Psychology
- Cognitive Neuroscience
Keywords
- analogical reasoning
- artificial intelligence
- learning
- self-explanation
- simulation
- thought experiments