Abstract
Learning defaults is a longstanding goal in the field of knowledge representation and reasoning. We provide a novel method for learning defaults by way of introducing a new predicate: the abnormal predicate, which explicitly covers all the exceptions to a rule, thus forming a default theory. Our proposed method for learning defaults is sound and complete for all rule-exceptions, and can be extended for use on other frameworks.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3 |
| Subtitle of host publication | ICAART |
| Editors | Ana Paula Rocha, Luc Steels, H. Jaap van den Herik |
| Publisher | SCITEPRESS |
| Pages | 892-900 |
| Number of pages | 9 |
| Volume | 3 |
| ISBN (Electronic) | 9789897587375 |
| DOIs | |
| Publication status | Published - 25 Feb 2025 |
| Event | 17th International Conference on Agents and Artificial Intelligence - Porto, Portugal Duration: 23 Feb 2025 → 25 Feb 2025 Conference number: 17 https://icaart.scitevents.org/?y=2025 |
Publication series
| Name | ICAART |
|---|---|
| Publisher | SciTePress |
| ISSN (Electronic) | 2184-433X |
Conference
| Conference | 17th International Conference on Agents and Artificial Intelligence |
|---|---|
| Abbreviated title | ICAART 2025 |
| Country/Territory | Portugal |
| City | Porto |
| Period | 23/02/25 → 25/02/25 |
| Internet address |
Keywords / Materials (for Non-textual outputs)
- logic and learning
- defaults
- knowledge representation