Multi-Agent Abstract Argumentation Frameworks With Incomplete Knowledge of Attacks
Authors: Andreas Herzig, Antonio Yuste Ginel
IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We introduce a multi-agent, dynamic extension of abstract argumentation frameworks (AFs), strongly inspired by epistemic logic, where agents have only partial information about the conflicts between arguments. This version of multi-agent AFs, as well as their updates with public announcements of attacks (more concretely, the effects of these updates on the acceptability of an argument) can be described using S5-PAL, a well-known dynamic-epistemic logic. Results will be stated throughout this paper without proof due to space limitations, but they can be found in Antonio Yuste Ginel s forthcoming Ph D dissertation. |
| Researcher Affiliation | Academia | Andreas Herzig1 and Antonio Yuste Ginel2 1IRIT, CNRS 2University of M alaga Andreas.Herzig@irit.fr, antonioyusteginel@gmail.com |
| Pseudocode | No | The paper describes a theoretical framework and its characterization using epistemic logic, but it does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described, nor does it state that code is released or available in supplementary materials. |
| Open Datasets | No | The paper is theoretical and does not involve empirical studies or datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical studies or datasets, therefore it does not provide dataset split information for validation. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require specific hardware for execution. |
| Software Dependencies | No | The paper describes a theoretical framework and its logical characterization, but it does not mention specific software dependencies or version numbers required to replicate any experiments or implementations. |
| Experiment Setup | No | The paper is theoretical and does not involve empirical experiments, therefore it does not provide specific experimental setup details like hyperparameters or training configurations. |