# Approximating Defeasible Logics to Improve Scalability

arXiv: https://arxiv.org/abs/2108.05232 · HTML: https://mlsanity.com/paper/2108.05232/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 23 references that are in the map.
- First posted on arXiv 11 Aug 2021.

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

- [Rethinking Defeasible Reasoning: A Scalable Approach](https://mlsanity.com/paper/2001.00406/) (2020)
- [Annotated Defeasible Logic](https://mlsanity.com/paper/1707.04734/) (2017)

## Abstract (arXiv)

Defeasible rules are used in providing computable representations of legal documents and, more recently, have been suggested as a basis for explainable AI. Such applications draw attention to the scalability of implementations. The defeasible logic DL(partial||) was introduced as a more scalable alternative to DL(partial), which is better known. In this paper we consider the use of (implementations of) DL(partial||) as a computational aid to computing conclusions in DL(partial) and other defeasible logics, rather than as an alternative to DL(partial). We identify conditions under which DL(partial||) can be substituted for DL(partial) with no change to the conclusions drawn, and conditions under which DL(partial||) can be used to draw some valid conclusions, leaving the remainder to be drawn by DL(partial).