Abstract
With only two to five slots of visual working memory (VWM), humans are able to quickly solve complex visual problems to near optimal solutions. To explain the paradox between tightly constrained VWM and impressively complex human visual problem-solving ability, we propose several principles for dynamic VWM allocation. In particular, we propose that complex visual information is represented in a temporal manner using only a few slots of VWM that include global and local visual chunks. We built a model of human traveling salesman problem solving based on these principles of VWM allocation and tested the model with eye-movement data. Exactly as the model predicted, human eye movements during traveling salesman problem solving have precise quantitative regularities with regard to both the general statistical pattern of attentional fixations and how they vary across individuals with different VWM capacities. Even though VWM capacity is very limited, eye movements dynamically allocate VWM resources to both local and global information, enabling attention to fine details without loss of the big picture.
Original language | English (US) |
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Pages (from-to) | 322-337 |
Number of pages | 16 |
Journal | Cognitive Science |
Volume | 34 |
Issue number | 2 |
DOIs | |
State | Published - Mar 2010 |
Externally published | Yes |
Keywords
- Complex problem solving
- Computational cognitive model
- Global visual information processing
- Visual working memory
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Cognitive Neuroscience
- Artificial Intelligence