Abstract
The cost increase of a learned rule in an explanation-based learning (EBL) system can be accurately analyzed by characterizing the learning process as a sequence of transformations from a problem solving episode to a learned rule. This approach protects an EBL system against the detrimental effects of the utility problem, where the cost of using learned knowledge overwhelms its benefits.
| Original language | English |
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| Pages | 1394 |
| Number of pages | 1 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 13th National Conference on Artificial Intelligence. Part 2 (of 2) - Portland, OR, USA Duration: 4 Aug 1996 → 8 Aug 1996 |
Conference
| Conference | Proceedings of the 1996 13th National Conference on Artificial Intelligence. Part 2 (of 2) |
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| City | Portland, OR, USA |
| Period | 4/08/96 → 8/08/96 |