Abstract
We present an improved computational model for performing geometric analogy. The model combines two previously modeled strategies and makes explicit claims about when people will use one strategy or the other. We compare the model to human performance on a classic problem set. The model’s strategy shifts, along with working memory load, account for most of the variance in human reaction times.
| Original language | English (US) |
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| Title of host publication | Building Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012 |
| Editors | Naomi Miyake, David Peebles, Richard P. Cooper |
| Publisher | The Cognitive Science Society |
| Pages | 701-706 |
| Number of pages | 6 |
| ISBN (Electronic) | 9780976831884 |
| State | Published - 2012 |
| Event | 34th Annual Meeting of the Cognitive Science Society: Building Bridges Across Cognitive Sciences Around the World, CogSci 2012 - Sapporo, Japan Duration: Aug 1 2012 → Aug 4 2012 |
Publication series
| Name | Building Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012 |
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Conference
| Conference | 34th Annual Meeting of the Cognitive Science Society: Building Bridges Across Cognitive Sciences Around the World, CogSci 2012 |
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| Country/Territory | Japan |
| City | Sapporo |
| Period | 8/1/12 → 8/4/12 |
Funding
This work was supported by NSF SLC Grant SBE-0541957, the Spatial Intelligence and Learning Center (SILC).
Keywords
- geometric analogy
- structure-mapping
- visual problem-solving
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Human-Computer Interaction
- Cognitive Neuroscience