Deductive and Abductive Reasoning with Causal and Evidential Information
Publication date
2020
Editors
Prakken, Henry
Bistarelli, Stefano
Santini, Francesco
Taticchi, Carlo
Advisors
Supervisors
Document Type
Part of book
Metadata
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License
cc_by_nc
Abstract
In this paper, we propose the information graph (IG) formalism, which provides a precise account of the interplay between deductive and abductive inference and causal and evidential information. IGs formalise analyses performed by domain experts in the informal reasoning tools they are familiar with, such as mind maps used in crime analysis. Based on principles for reasoning with causal and evidential information given the evidence, we impose constraints on the inferences that may be performed with IGs. Moreover, we propose an argumentation formalism based on IGs that allows arguments to be formally evaluated.
Keywords
Deduction, Abduction, Causal and evidential information, Argumentation, SDG 16 - Peace, Justice and Strong Institutions
Citation
Wieten, G M, Bex, F J, Prakken, H & Renooij, S 2020, Deductive and Abductive Reasoning with Causal and Evidential Information. in H Prakken, S Bistarelli, F Santini & C Taticchi (eds), Computational Models of Argument : Proceedings of COMMA 2020. Frontiers in Artificial Intelligence and Applications, vol. 326, IOS Press, Amsterdam, pp. 383-394. https://doi.org/10.3233/FAIA200522