AIJul 8, 2020
Dung's semantics satisfy attack removal monotonicity
arXiv:2007.04221v12 citations
AI Analysis
This addresses a theoretical problem in formal argumentation for AI researchers, but it is incremental as it confirms known properties rather than introducing new methods.
The paper tackled the problem of verifying monotonicity properties in argumentation semantics, specifically showing that preferred, stable, complete, and grounded semantics satisfy attack removal monotonicity, meaning that removing an attack does not worsen the acceptance status of arguments.
We show that preferred, stable, complete, and grounded semantics satisfy attack removal monotonicity. This means that if an attack from b to a is removed, the status of a cannot worsen, e.g. if a was skeptically accepted, it cannot become rejected.