Preferential reasoning with typicality and neural network models (Extended abstract)

Laura GIORDANO; V. Gliozzi; Daniele THESEIDER DUPRE'

Preferential reasoning with typicality and neural network models (Extended abstract)

Department of Science and Technological Innovation

Research output: Contribution to conference › Paper › peer-review

Abstract

In this extended abstract we report some results concerning the relationships between a multipreferentia semantics for defeasible reasoning in knowledge representation and some neural network models, namel Self-Organising Maps and Multilayer Perceptrons.

Original language	English
Pages	83-89
Number of pages	7
Publication status	Published - 2021
Event	3rd Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis, OVERLAY 2021 - ita Duration: 1 Jan 2021 → …

Conference

Conference	3rd Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis, OVERLAY 2021
City	ita
Period	1/01/21 → …

Keywords

Common sense reasoning
Neural networks
Preferential semantics
Weighted conditionals

Access to Document

http://hdl.handle.net/11579/135287

Cite this

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title = "Preferential reasoning with typicality and neural network models (Extended abstract)",

abstract = "In this extended abstract we report some results concerning the relationships between a multipreferentia semantics for defeasible reasoning in knowledge representation and some neural network models, namel Self-Organising Maps and Multilayer Perceptrons.",

keywords = "Common sense reasoning, Neural networks, Preferential semantics, Weighted conditionals, Common sense reasoning, Neural networks, Preferential semantics, Weighted conditionals",

author = "Laura GIORDANO and V. Gliozzi and \{THESEIDER DUPRE'\}, Daniele",

year = "2021",

language = "English",

pages = "83--89",

note = "3rd Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis, OVERLAY 2021 ; Conference date: 01-01-2021",

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TY - CONF

T1 - Preferential reasoning with typicality and neural network models (Extended abstract)

AU - GIORDANO, Laura

AU - Gliozzi, V.

AU - THESEIDER DUPRE', Daniele

PY - 2021

Y1 - 2021

N2 - In this extended abstract we report some results concerning the relationships between a multipreferentia semantics for defeasible reasoning in knowledge representation and some neural network models, namel Self-Organising Maps and Multilayer Perceptrons.

AB - In this extended abstract we report some results concerning the relationships between a multipreferentia semantics for defeasible reasoning in knowledge representation and some neural network models, namel Self-Organising Maps and Multilayer Perceptrons.

KW - Common sense reasoning

KW - Neural networks

KW - Preferential semantics

KW - Weighted conditionals

KW - Common sense reasoning

KW - Neural networks

KW - Preferential semantics

KW - Weighted conditionals

UR - https://iris.uniupo.it/handle/11579/135287

M3 - Paper

SP - 83

EP - 89

T2 - 3rd Workshop on Artificial Intelligence and Formal Verification, Logic, Automata, and Synthesis, OVERLAY 2021

Y2 - 1 January 2021

ER -

Preferential reasoning with typicality and neural network models (Extended abstract)

Abstract

Conference

Keywords

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Cite this