# Forgetting in Answer Set Programming -- A Survey

arXiv: https://arxiv.org/abs/2107.07016 · HTML: https://mlsanity.com/paper/2107.07016/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 104 references that are in the map.
- First posted on arXiv 14 Jul 2021.

## Builds on (most cited first, 6 of 6)

- [Modularity Aspects of Disjunctive Stable Models](https://mlsanity.com/paper/1401.3484/) (2014)
- [Omission-based Abstraction for Answer Set Programs](https://mlsanity.com/paper/2004.01410/) (2020)
- [A Syntactic Operator for Forgetting that Satisfies Strong Persistence](https://mlsanity.com/paper/1907.12501/) (2019)
- [When You Must Forget: beyond strong persistence when forgetting in answer set programming](https://mlsanity.com/paper/1707.05152/) (2017)
- [Interpolable Formulas in Equilibrium Logic and Answer Set Programming](https://mlsanity.com/paper/1401.3897/) (2014)
- [The Logical Difference for the Lightweight Description Logic EL](https://mlsanity.com/paper/1401.5850/) (2014)

## Built on by (most cited first, 5 of 5)

- [Dual Forgetting Operators in the Context of Weakest Sufficient and Strongest Necessary Conditions](https://mlsanity.com/paper/2305.07233/) (2023)
- [A Unified View on Forgetting and Strong Equivalence Notions in Answer Set Programming](https://mlsanity.com/paper/2312.07993/) (2023)
- [Abductive forgetting](https://mlsanity.com/paper/2209.12825/) (2022)
- [Techniques for Measuring the Inferential Strength of Forgetting Policies](https://mlsanity.com/paper/2404.02454/) (2024)
- [Interpolation in Knowledge Representation](https://mlsanity.com/paper/2512.08833/) (2025)

## Abstract (arXiv)

Forgetting - or variable elimination - is an operation that allows the removal, from a knowledge base, of middle variables no longer deemed relevant. In recent years, many different approaches for forgetting in Answer Set Programming have been proposed, in the form of specific operators, or classes of such operators, commonly following different principles and obeying different properties. Each such approach was developed to address some particular view on forgetting, aimed at obeying a specific set of properties deemed desirable in such view, but a comprehensive and uniform overview of all the existing operators and properties is missing. In this paper, we thoroughly examine existing properties and (classes of) operators for forgetting in Answer Set Programming, drawing a complete picture of the landscape of these classes of forgetting operators, which includes many novel results on relations between properties and operators, including considerations on concrete operators to compute results of forgetting and computational complexity. Our goal is to provide guidance to help users in choosing the operator most adequate for their application requirements.