Abstract
People can often learn new tasks quickly. This is hard to explain with cognitive models because they either need extensive task-specific knowledge or a long training session. In this article, we try to solve this by proposing that task knowledge can be decomposed into skills. A skill is a task-independent set of knowledge that can be reused for different tasks. As a demonstration, we created an attentional blink model from the general skills that we extracted from models of visual attention and working memory. The results suggest that this is a feasible modeling method, which could lead to more generalizable models.
Original language | English |
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Pages (from-to) | 1030-1045 |
Number of pages | 16 |
Journal | Topics in Cognitive Science |
Volume | 12 |
Issue number | 3 |
DOIs | |
Publication status | Published - 17-Jul-2020 |
Keywords
- Attentional blink
- PRIMs
- ACT-R
- Skill-based modeling
- Cognitive model
- Instruction learning
- Skill-based approach
- Cognitive architectures
- INDIVIDUAL-DIFFERENCES
- INTEGRATED THEORY