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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1974/1268
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| Title: | A radial basis memory model for human maze learning |
| Authors: | Drewell, Lisa Y. |
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| Keywords: | Memory model
Maze
Radial basis functions
Learning
Navigation |
| Issue Date: | 2008 |
| Series/Report no.: | Canadian theses |
| Abstract: | This research develops a memory model capable of performing in a human-like fashion on a maze traversal task. The model is based on and retains the underlying ideas of Minerva 2 but is executed with different mathematical operations and with some added parameters and procedures that enable more capabilities. When applied to the same maze traversal task as was used in a previous experiment with human subjects, the performance of a maze traversal agent with the developed model as its memory emulated the error rates of the human data remarkably well. As well, the maze traversal agent and memory model successfully emulated the human data when it was divided into two groups: fast maze learners and slow maze learners. It was able to account for individual differences in performance, specifically, individual differences in the learning rate. Because forgetting was not applied and therefore all experiences were flawlessly encoded in memory, the model additionally demonstrates that error can be due to interference between memories rather than forgetting. |
| Description: | Thesis (Master, Computing) -- Queen's University, 2008-06-04 13:39:38.179 |
| URI: | http://hdl.handle.net/1974/1268 |
| Appears in Collections: | Queen's Theses & Dissertations
Computing Graduate Theses
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