Abstract
The ABC system supports analogical abduction algorithms for knowledge transfer, e.g., existing logical rules are adapted, by reformation, into new rules by substituting symbols for similar ones. Although such knowledge transfer method can easily expand knowledge sets, it is likely to produce inconsistent knowledge, e.g., equations that do not fit target data in the real world. To solve this problem, we extend the classic reformation algorithm to repair numerical equations that violate target data. Equation reformation is achieved by weakening equation parameters when unblocking failed SLD-resolution proofs. The feasibility of numerical equation reformation is demonstrated by the automated repair of a faulty electrostatic force equation that is analogically transferred from the gravity equation.
Original language | English |
---|---|
Title of host publication | Proceedings of the 3rd Human-Like Computing Workshop (HLC 2022) |
Editors | Alan Bundy, Denis Mareschal |
Publisher | CEUR-WS |
Pages | 18-23 |
Number of pages | 6 |
Volume | 3227 |
Publication status | Published - 2022 |
Externally published | Yes |
Event | International Workshop on Human-Like Computing Workshop 2022 - Windsor, United Kingdom Duration: 28 Sept 2022 → 30 Sept 2022 Conference number: 3rd https://ceur-ws.org/Vol-3227/ (Proceedings) https://ijclr22.doc.ic.ac.uk/hlc2022.html/index.html#:~:text=The%203rd%20International%20Workshop%20on,%2C%2028%2D30%20September%202022. (Website) |
Publication series
Name | CEUR Workshop Proceedings |
---|---|
Publisher | CEUR-WS |
ISSN (Print) | 1613-0073 |
Conference
Conference | International Workshop on Human-Like Computing Workshop 2022 |
---|---|
Abbreviated title | HLC 2022 |
Country/Territory | United Kingdom |
City | Windsor |
Period | 28/09/22 → 30/09/22 |
Internet address |
Keywords
- Analogical reasoning
- Knowledge transfer
- Reformation
- Theory repair