Control Argumentation Frameworks
Authors: Yannis Dimopoulos, Jean-Guy Mailly, Pavlos Moraitis
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This work proposes Control Argumentation Frameworks (CAFs), a new approach that generalizes existing techniques, namely normal extension enforcement, by accommodating the possibility of uncertainty in dynamic scenarios. A QBF encoding of reasoning with CAFs provides a computational mechanism for determining whether and how this goal can be reached. We also provide some results concerning soundness and completeness of the proposed encoding as well as complexity issues. |
| Researcher Affiliation | Academia | Yannis Dimopoulos Department of Computer Science University of Cyprus yannis@cs.ucy.ac.cy Jean-Guy Mailly LIPADE Paris Descartes University, France jean-guy.mailly@parisdescartes.fr Pavlos Moraitis LIPADE Paris Descartes University, France pavlos@mi.parisdescartes.fr |
| Pseudocode | Yes | Algorithm 1 CAFControl Require: CAF = F, C, U , T AF , x {sk, cr} QBFsk(CAF, T) is the formula defined by (1) QBFcr(CAF, T) is the formula defined by (2) if QBFTruth(QBFx(CAF, T)) then Aconf = {xi AC | onxi is assigned 1 in QBFModel(QBFx(CAF, T))} return Aconf else return end if |
| Open Source Code | No | The paper does not contain any statement about releasing open-source code for the methodology, nor does it provide a link to a code repository. |
| Open Datasets | No | The paper is theoretical and focuses on developing a new argumentation framework and its logical encoding. It does not mention or use any specific datasets for training, validation, or testing. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments involving dataset splits for training, validation, or testing. Therefore, no specific dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and does not describe empirical experiments that would require specific hardware. Therefore, no hardware specifications are mentioned. |
| Software Dependencies | No | The paper mentions using "QBFs" and refers to "QBF solvers" (Pulina 2016), but it does not specify any particular QBF solver by name with a version number, or other software dependencies with versions required for reproducibility. |
| Experiment Setup | No | The paper is theoretical and focuses on formal definitions, logical encodings, and complexity analysis. It does not describe any empirical experimental setup, hyperparameters, or training configurations. |