DATALOG+/- ARGUMENTATION GRAPH GENERATOR (DAGGER)

Bruno Yun, Madalina Croitoru, Pierre Bisquert and Srdjan Vesic

DAGGER is a generator for logic-based argumentation frameworks. It takes as input a knowledge base in DLGP format, allows to generate/visualise the corresponding argumentation graph, and download it in the Aspartix format.

DAGGER captures the deductive argumentation framework of Croitoru et al. (2013) and the maximal consistent sets (or repairs) of the knowledge base.

The layered architecture is as follows:

High level: the graphical user interface.
Mid level: the logical model (knowledge bases and argumentation frameworks) and their visualisations.
Low level: the computational tools.

The User interacts with the GUI by providing a knowledge base and a computation order. Then, the GUI communicates with the GRAAL library which possesses the toolkit for handling existential rules knowledge bases. Then, it generates repairs for the argument generation. The latter enables the argument filtration process and the attack generation. Next, the argumentation graph is displayed graphically using the GrahStream library and textually using the Aspartix format.

Each layer is composed of modules and some modules are composed of sub-modules. The information flow passes from the high level to the low level through the intermediate level using the different links between modules.

Git Repository

The git repository is accessible online at the LIRMM’s gitlab.

If you use the DAGGER tool in your academic work, please cite: DAGGE DAGGER-Datalog-Argumentation_Graph_GEneRator R: Datalog+/- Argumentation Graph GEneRator, Bruno Yun, Madalina Croitoru, Pierre Bisquert and Srdjan Vesic, AAMAS 2018.