Dettagli rapporto tecnico
| Autori: | Laura Giordano |
| Daniele Theseider Dupré |
| Area Scientifica: | Artificial Intelligence |
| Logic-Based Reasoning |
| Neural Networks |
| Titolo: | Weighted defeasible knowledge bases and a multipreference semantics for a deep neural network model |
| Apparso su: | TR-INF-2020-12-05-UNIPMN |
| Editore: | DiSIT, Computer Science Institute, UPO |
| Anno: | 2020 |
| URL: | http://www.di.unipmn.it...R-INF-2020-12-05-UNIPMN.pdf |
| Sommario: | In this paper we investigate the relationships between a multipreferential semantics for defeasible reasoning in knowledge representation and a deep neural network model. Weighted knowledge bases for description logics are considered under a ``concept-wise" multipreference semantics. The semantics is further extended to fuzzy interpretations and exploited to provide a preferential interpretation of Multilayer Perceptrons. |
