An Extension-Based Approach to Belief Revision in Abstract Argumentation
Authors: Martin Diller, Adrian Haret, Thomas Linsbichler, Stefan Rümmele, Stefan Woltran
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we present a generic solution to this problem which applies to many prominent I-maximal argumentation semantics. In order to prove a full representation theorem, we make use of recent advances in both areas of argumentation and belief change. In particular, we utilize the concepts of realizability in argumentation and the notion of compliance as used in Horn revision. Our main contributions are as follows: We derive full representation theorems for both mentioned types of revision; our results are, moreover, generic in the sense that they hold for a wide range of semantics including preferred, semi-stable, stage, and stable semantics. |
| Researcher Affiliation | Academia | Martin Diller, Adrian Haret, Thomas Linsbichler, Stefan R ummele, and Stefan Woltran {diller,haret,linsbich,ruemmele,woltran}@dbai.tuwien.ac.at Institute of Information Systems Vienna University of Technology, Austria |
| Pseudocode | No | The paper contains definitions, theorems, proofs, and lemmas, but no pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any statements or links indicating the availability of open-source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper and does not involve experimental evaluation on datasets, hence no information about public datasets for training is provided. |
| Dataset Splits | No | This is a theoretical paper and does not involve experimental evaluation on datasets, hence no information about dataset splits for training, validation, or testing is provided. |
| Hardware Specification | No | This is a theoretical paper and does not report any computational experiments, thus no hardware specifications are mentioned. |
| Software Dependencies | No | This is a theoretical paper and does not report any computational experiments, thus no software dependencies with specific version numbers are mentioned. |
| Experiment Setup | No | This is a theoretical paper and does not report any experiments, thus no experimental setup details like hyperparameters or training configurations are provided. |