Published in

Proceedings of the 31st Annual ACM/IEEE Symposium on Logic in Computer Science - LICS '16

DOI: 10.1145/2933575.2934568

Association for Computing Machinery (ACM), ACM Transactions on Computational Logic, 3(19), p. 1-24, 2018

DOI: 10.1145/3226594

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Interaction Graphs

Journal article published in 2016 by Thomas Seiller ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Interaction graphs were introduced as a general, uniform, construction of dynamic models of linear logic, encompassing all Geometry of Interaction (GoI) constructions introduced so far. This series of work was inspired from Girard's hyperfinite GoI, and develops a quantitative approach that should be understood as a dynamic version of weighted relational models. Until now, the interaction graphs framework has been shown to deal with exponentials for the constrained system ELL (Elementary Linear Logic) while keeping its quantitative aspect. Adapting older constructions by Girard, one can clearly define "full" exponentials, but at the cost of these quantitative features. We show here that allowing interpretations of proofs to use continuous (yet finite in a measure-theoretic sense) sets of states, as opposed to earlier Interaction Graphs constructions were these sets of states were discrete (and finite), provides a model for full linear logic with second order quantification.