AGM Meets Abstract Argumentation: Expansion and Revision for Dung Frameworks

Authors: Ringo Baumann, Gerhard Brewka

IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper we combine two of the most important areas of knowledge representation, namely belief revision and (abstract) argumentation. More precisely, we show how AGM-style expansion and revision operators can be defined for Dung s abstract argumentation frameworks (AFs). Our approach is based on a reformulation of the original AGM postulates for revision in terms of monotonic consequence relations for AFs. The latter are defined via a new family of logics, called Dung logics, which satisfy the important property that ordinary equivalence in these logics coincides with strong equivalence for the respective argumentation semantics. Based on these logics we define expansion as usual via intersection of models. We show the existence of such operators. This is far from trivial and requires to study realizability in the context of Dung logics. We then study revision operators. We show why standard approaches based on a distance measure on models do not work for AFs and present an operator satisfying all postulates for a specific Dung logic.
Researcher Affiliation Academia Ringo Baumann and Gerhard Brewka Computer Science Institute, Leipzig University, Germany {baumann,brewka}@informatik.uni-leipzig.de
Pseudocode No The paper does not contain any pseudocode or clearly labeled algorithm blocks.
Open Source Code No The paper does not provide any information about open-source code for the described methodology.
Open Datasets No The paper is theoretical and does not utilize publicly available datasets for experimental training. The examples provided (e.g., Example 1) are for theoretical illustration, not empirical data.
Dataset Splits No The paper is theoretical and does not involve dataset splits for validation or other experimental procedures.
Hardware Specification No The paper describes theoretical work and does not mention any hardware specifications used for experiments.
Software Dependencies No The paper describes theoretical work and does not mention specific software dependencies with version numbers.
Experiment Setup No The paper describes theoretical work and does not detail any experimental setup or hyperparameters.