On Computing Explanations in Argumentation
Authors: Xiuyi Fan, Francesca Toni
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we propose a new argumentation semantics, related admissibility, designed for giving explanations to arguments in both Abstract Argumentation and Assumption-based Argumentation. We identify different types of explanations deļ¬ned in terms of the new semantics. We also give a correct computational counterpart for explanations using dispute forests. |
| Researcher Affiliation | Academia | Xiuyi Fan and Francesca Toni {x.fan09,f.toni}@imperial.ac.uk Department of Computing, Imperial College London, SW7 2AZ, UK |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for validation or training. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper describes theoretical concepts and does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not include details about an experimental setup, hyperparameters, or training configurations. |