Multilayer Perceptrons as Weighted Conditional Knowledge Bases: An Overview

Laura Giordano; Daniele Theseider Dupré

Multilayer Perceptrons as Weighted Conditional Knowledge Bases: An Overview

Dipartimento di Scienze e Innovazione Tecnologica

Risultato della ricerca: Contributo su rivista › Articolo da conferenza › peer review

Abstract

In this paper we report about the relationships between a multi-preferential semantics for defeasible description logics and a deep neural network model. Weighted knowledge bases for description logics are considered under a “concept-wise" preferential semantics, which is further extended to fuzzy interpretations and exploited to provide a preferential interpretation of Multilayer Perceptrons.

Lingua originale	Inglese
pagine (da-a)	10-18
Numero di pagine	9
Rivista	CEUR Workshop Proceedings
Volume	3078
Stato di pubblicazione	Pubblicato - 2022
Evento	2021 International Conference of the Italian Association for Artificial Intelligence, AIxIA 2021 DP - Virtual, Online Durata: 1 dic 2021 → 3 dic 2021

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abstract = "In this paper we report about the relationships between a multi-preferential semantics for defeasible description logics and a deep neural network model. Weighted knowledge bases for description logics are considered under a “concept-wise{"} preferential semantics, which is further extended to fuzzy interpretations and exploited to provide a preferential interpretation of Multilayer Perceptrons.",

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AU - Dupré, Daniele Theseider

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PY - 2022

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N2 - In this paper we report about the relationships between a multi-preferential semantics for defeasible description logics and a deep neural network model. Weighted knowledge bases for description logics are considered under a “concept-wise" preferential semantics, which is further extended to fuzzy interpretations and exploited to provide a preferential interpretation of Multilayer Perceptrons.

AB - In this paper we report about the relationships between a multi-preferential semantics for defeasible description logics and a deep neural network model. Weighted knowledge bases for description logics are considered under a “concept-wise" preferential semantics, which is further extended to fuzzy interpretations and exploited to provide a preferential interpretation of Multilayer Perceptrons.

KW - Common sense reasoning

KW - Neural networks

KW - Preferential semantics

KW - Weighted conditionals

UR - https://www.scopus.com/pages/publications/85124381679

M3 - Conference article

AN - SCOPUS:85124381679

SN - 1613-0073

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JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

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Multilayer Perceptrons as Weighted Conditional Knowledge Bases: An Overview

Abstract

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