Informational Semantics as a Third Alternative?

Abstract

Informational semantics were first developed as an interpretation of the model-theory of substructural (and especially relevant) logics. In this paper we argue that such a semantics is of independent value and that it should be considered as a genuine alternative explication of the notion of logical consequence alongside the traditional model-theoretical and the proof-theoretical accounts. Our starting point is the content-nonexpansion platitude which stipulates that an argument is valid iff the content of the conclusion does not exceed the combined content of the premises. We show that this basic platitude can be used to characterise the extension of classical as well as non-classical consequence relations. The distinctive trait of an informational semantics is that truth-conditions are replaced by information-conditions. The latter leads to an inversion of the usual order of explanation: Considerations about logical discrimination (how finely propositions are individuated) are conceptually prior to considerations about deductive strength. Because this allows us to bypass considerations about truth, an informational semantics provides an attractive and metaphysically unencumbered account of logical consequence, nonclassical logics, logical rivalry and pluralism about logical consequence.

Philosophical Perspectives

“…Good introductory reading includes Priest (2008) and Read (1995). Nice advanced pieces include Van Benthem and Martinez (2008) and Allo and Mares (2012).…”

A Taxonomy of Errors for Information Systems

“…4 For the logic of being informed that applies at the level of goals, see [11]. In the next section, we will explore the epistemic and semantic space included between knowledge and ignorance and characterize it as the scope where errors occur.…”

Judgement aggregation in non-classical logics

“…In particular, relevant logics reject the axiom A → (B → A) that means that whenever A holds, A can be implied by any B, regardless of the relevance of B for assessing A. Relevant logics have also been motivated as logics for modelling epistemic agents and as logics that model inferences that depend on the amount of information available to cognitive agents, Allo and Mares (2012); Mares (2004); Masolo and Porello (2015).…”