A Quantitative-Informational Approach to Logical Consequence

In this chapter, we propose a definition of logical consequence based on the relation between the quantity of information present in a particular set of formulae and a particular formula. As a starting point, we use Shannon’s quantitative notion of information, founded on the concepts of logarithmic...

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Detalles Bibliográficos
Autores: Alves, Marcos Antonio [UNESP], Loffredo D’Ottaviano, Itala M.
Tipo de recurso: capítulo de libro
Estado:Versión publicada
Fecha de publicación:2015
País:Brasil
Institución:Universidade Estadual Paulista (UNESP)
Repositorio:Repositório Institucional da UNESP
Idioma:inglés
OAI Identifier:oai:repositorio.unesp.br:11449/205139
Acceso en línea:http://dx.doi.org/10.1007/978-3-319-15368-1_3
http://hdl.handle.net/11449/205139
Access Level:acceso abierto
Palabra clave:Information
Informational logical consequence
Logical consequence
Nonclassical logics
Paraconsistent logic
Probability
Semantics
Descripción
Sumario:In this chapter, we propose a definition of logical consequence based on the relation between the quantity of information present in a particular set of formulae and a particular formula. As a starting point, we use Shannon’s quantitative notion of information, founded on the concepts of logarithmic function and probability value. We first consider some of the basic elements of an axiomatic probability theory, and then construct a probabilistic semantics for languages of classical propositional logic. We define the quantity of information for the formulae of these languages and introduce the concept of informational logical consequence, identifying some important results; among them certain arguments that have traditionally been considered valid, such as modus ponens, are not valid from the informational perspective; the logic underlying informational logical consequence is not classical, and is at the least paraconsistent sensu lato; informational logical consequence is not a Tarskian logical consequence.