Rerepresenting and Restructuring Domain Theories: A Constructive Induction Approach
| dc.creator | Donoho, S. K. | |
| dc.creator | Rendell, L. A. | |
| dc.date | 1995-04-01 | |
| dc.date.accessioned | 2026-07-07T09:12:19Z | |
| dc.date.available | 2026-07-07T09:12:19Z | |
| dc.description | Theory revision integrates inductive learning and background knowledge by combining training examples with a coarse domain theory to produce a more accurate theory. There are two challenges that theory revision and other theory-guided systems face. First, a representation language appropriate for the initial theory may be inappropriate for an improved theory. While the original representation may concisely express the initial theory, a more accurate theory forced to use that same representation may be bulky, cumbersome, and difficult to reach. Second, a theory structure suitable for a coarse domain theory may be insufficient for a fine-tuned theory. Systems that produce only small, local changes to a theory have limited value for accomplishing complex structural alterations that may be required. Consequently, advanced theory-guided learning systems require flexible representation and flexible structure. An analysis of various theory revision systems and theory-guided learning systems reveals specific strengths and weaknesses in terms of these two desired properties. Designed to capture the underlying qualities of each system, a new system uses theory-guided constructive induction. Experiments in three domains show improvement over previous theory-guided systems. This leads to a study of the behavior, limitations, and potential of theory-guided constructive induction. | |
| dc.description | See http://www.jair.org/ for an online appendix and other files accompanying this article | |
| dc.identifier | https://arxiv.org/abs/cs/9504101 | |
| dc.identifier | http://arxiv.org/abs/cs/9504101 | |
| dc.identifier | Journal of Artificial Intelligence Research, Vol 2, (1995), 411-446 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/151982 | |
| dc.subject | Artificial Intelligence | |
| dc.title | Rerepresenting and Restructuring Domain Theories: A Constructive Induction Approach | |
| dc.type | text |