Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Two Sides of the Same Coin: Belief Revision and Enforcing Arguments
Authors: Adrian Haret, Johannes P. Wallner, Stefan Woltran
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our analysis of enforcing arguments proceeds by (i) axiomatizing it as an operation in propositional logic and providing a representation result in terms of rankings on sets of interpretations, (ii) showing that it stands in close relationship to belief revision, and (iii) using it as a gateway towards a principled treatment of enforcement in abstract argumentation. |
| Researcher Affiliation | Academia | Adrian Haret, Johannes P. Wallner, and Stefan Woltran Institute of Logic and Computation, TU Wien, Austria |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use datasets; therefore, no information on public dataset access is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for experiments. |
| Hardware Specification | No | The paper is theoretical and does not describe experiments that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not specify software dependencies with version numbers for reproducibility of experiments. |
| Experiment Setup | No | The paper is theoretical and does not provide details on an experimental setup, hyperparameters, or training configurations. |