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Going beyond the more classically studied reasoning problems over argumentation frameworks (AFs), the study of dynamics in argumentation gives rise to new types of computational challenges. This work studies ways of extending the scalability of computational approaches to reasoning about dynamics of abstract argumentation frameworks. In particular, we focus on three recently proposed optimization problems underlying AF dynamics—two variants of enforcement in abstract argumentation and the synthesis of argumentation frameworks from examples—for semantics under which the problems are (presumably) complete for the second level of the polynomial hierarchy. As the main contributions, we show that by bridging recent theoretical results on the persistence of extensions under changes to the structure of AFs with Boolean satisfiability (SAT) counterexample-guided abstraction refinement algorithms for the considered problems, the scalability of state-of-the-art practical algorithms for each of the three problems can be significantly improved.
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