TY - GEN
T1 - Weighted Defeasible Knowledge Bases and a Multipreference Semantics for a Deep Neural Network Model
AU - Giordano, Laura
AU - Theseider Dupré, Daniele
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - 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, under some condition.
AB - 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, under some condition.
UR - http://www.scopus.com/inward/record.url?scp=85111126198&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-75775-5_16
DO - 10.1007/978-3-030-75775-5_16
M3 - Conference contribution
AN - SCOPUS:85111126198
SN - 9783030757748
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 225
EP - 242
BT - Logics in Artificial Intelligence - 17th European Conference, JELIA 2021, Proceedings
A2 - Faber, Wolfgang
A2 - Friedrich, Gerhard
A2 - Gebser, Martin
A2 - Morak, Michael
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th European Conference on Logics in Artificial Intelligence, JELIA 2021
Y2 - 17 May 2021 through 20 May 2021
ER -