# ABA Learning via ASP

arXiv: https://arxiv.org/abs/2308.15877 · HTML: https://mlsanity.com/paper/2308.15877/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 19 references that are in the map.
- First posted on arXiv 30 Aug 2023.

## Builds on (most cited first, 2 of 2)

- [A New Algorithm to Automate Inductive Learning of Default Theories](https://mlsanity.com/paper/1707.02693/) (2017)
- [Learning Assumption-based Argumentation Frameworks](https://mlsanity.com/paper/2305.15921/) (2023)

## Built on by (most cited first, 4 of 4)

- [Learning Brave Assumption-Based Argumentation Frameworks via ASP](https://mlsanity.com/paper/2408.10126/) (2024)
- [Argumentation and Machine Learning](https://mlsanity.com/paper/2410.23724/) (2024)
- [Object-Centric Neuro-Argumentative Learning](https://mlsanity.com/paper/2506.14577/) (2025)
- [Object-Centric Case-Based Reasoning via Argumentation](https://mlsanity.com/paper/2510.00185/) (2025)

## Abstract (arXiv)

Recently, ABA Learning has been proposed as a form of symbolic machine learning for drawing Assumption-Based Argumentation frameworks from background knowledge and positive and negative examples. We propose a novel method for implementing ABA Learning using Answer Set Programming as a way to help guide Rote Learning and generalisation in ABA Learning.