Abstract
Artificial intelligence systems use an increasing amount of computation and data to solve very specific problems. By contrast, human minds solve a wide range of problems using a fixed amount of computation and limited experience. We identify two abilities that we see as crucial to this kind of general intelligence: meta-reasoning (deciding how to allocate computational resources) and meta-learning (modeling the learning environment to make better use of limited data). We summarize the relevant AI literature and relate the resulting ideas to recent work in psychology.
Original language | English (US) |
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Pages (from-to) | 24-30 |
Number of pages | 7 |
Journal | Current Opinion in Behavioral Sciences |
Volume | 29 |
DOIs | |
State | Published - Oct 2019 |
All Science Journal Classification (ASJC) codes
- Cognitive Neuroscience
- Psychiatry and Mental health
- Behavioral Neuroscience