Proceedings

Stratified Evidence Logics

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Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence. Main track. Pages 1523-1529.

https://doi.org/10.24963/ijcai.2019/211

Abstract

Evidence logics model agents' belief revision process as they incorporate and aggregate information obtained from multiple sources.

This information is captured using neighbourhood structures, where individual neighbourhoods represent pieces of evidence.

In this paper we propose an extended framework which allows one to explicitly quantify either the number of evidence sets, or effort, needed to justify a given proposition, provide a complete deductive calculus and a proof of decidability, and show how existing frameworks can be embedded into ours.

Philippe Balbiani, David Fernández-Duque, Andreas Herzig, and Emiliano Lorini. 2019. Stratified Evidence Logics. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19. IJCAI, 1523–1529. https://doi.org/10.24963/ijcai.2019/211
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