Facilitating DL-based hybrid reasoning with inference fusion.
Hu, Bo; Arana, Inés; Compatangelo, Ernesto
We present an extension to DL-based taxonomic reasoning by means of inference fusion, i.e. the dynamic combination of inferences from distributed heterogeneous reasoners. Our approach integrates results from a DL-based system with results from a constraint solver under the direction of a global reasoning coordinator. Inference fusion is performed by (i) processing heterogeneous input knowledge, producing suitable homogeneous input knowledge for each specialised reasoner; (ii) activating each reasoner when necessary, collecting its results and passing them to the other reasoner if appropriate; (iii) combining the results of the two reasoners. We discuss the benefits of our approach and demonstrate our ideas by proposing a language ( (D)/S) and a reasoning system (Concor) which uses knowledge bases written in (D)/S and supports hybrid reasoning. We illustrate our ideas with an example.
|Journal Article Type||Conference Paper|
|Start Date||Dec 10, 2002|
|Publication Date||Jul 31, 2003|
|Peer Reviewed||Peer Reviewed|
|Institution Citation||HU, B., ARANA, I. and COMPATANGELO, E. 2003. Facilitating DL-based hybrid reasoning with inference fusion. Knowledge-based systems [online], 16(5-6): proceedings of the 22nd British Computer Society Specialist Group on Artificial Intelligence (SGAI) international conference on knowledge-based systems and applied artificial intelligence (ES2002), 10-12 December 2002, Cambridge, UK, pages 42-48. Available from: https://doi.org/10.1016/S0950-7051(03)00026-1|
|Keywords||Descriptive logics; Hybrid reasoning; Constraint reasoning|
HU 2003 Facilitating DL-based hybrid
You might also like
Real-time relative permeability prediction using deep learning.
A hybrid approach to solving coarse-grained DisCSPs.
Presentation / Conference
DynABT: dynamic asynchronous backtracking for dynamic DisCSPs.