Web-based Argumentation

TL;DR

This paper presents a Python-based web-accessible solver for Assumption-Based Argumentation (ABA), capable of computing multiple semantics and providing visualizations, thus making ABA more accessible and easier to analyze.

Contribution

Developed the first web interface for an ABA solver in Python that computes various semantics, improving accessibility and performance over existing solvers.

Findings

Achieved lower average runtime than proxdd with optimal configurations.

Successfully computed multiple semantics including conflict-free, stable, and grounded.

Encountered more exceptions, likely due to computing more semantics.

Abstract

Assumption-Based Argumentation (ABA) is an argumentation framework that has been proposed in the late 20th century. Since then, there was still no solver implemented in a programming language which is easy to setup and no solver have been interfaced to the web, which impedes the interests of the public. This project aims to implement an ABA solver in a modern programming language that performs reasonably well and interface it to the web for easier access by the public. This project has demonstrated the novelty of development of an ABA solver, that computes conflict-free, stable, admissible, grounded, ideal, and complete semantics, in Python programming language which can be used via an easy-to-use web interface for visualization of the argument and dispute trees. Experiments were conducted to determine the project's best configurations and to compare this project with proxdd, a state-of-the-art ABA solver, which has no web interface and computes less number of semantics. From the results of the experiments, this project's best configuration is achieved by utilizing "pickle" technique and tree caching technique. Using this project's best configuration, this project achieved a lower average runtime compared to proxdd. On other aspect, this project encountered more cases with exceptions compared to proxdd, which might be caused by this project computing more semantics and hence requires more resources to do so. Hence, it can be said that this project run comparably well to the state-of-the-art ABA solver proxdd. Future works of this project include computational complexity analysis and efficiency analysis of algorithms implemented, implementation of more semantics in argumentation framework, and usability testing of the web interface.