Choosing the Lens: Strategic Perspective Activation in Context-Dependent Argumentation
2026-05-29 • Artificial Intelligence
Artificial Intelligence
AI summaryⓘ
The authors propose a new way to think about arguments that change depending on outside conditions, called context-dependent argumentation frameworks (CDAFs). They build on an existing theory by allowing the success of attacks between arguments to vary with context, controlled by what the agent can do and what priorities are set. Their example shows that an argument might fail under all full priority settings but succeed if only some parts are active, highlighting new strategic possibilities. They also study the complexity of deciding such manipulations but leave some questions open for future work.
Dung's argumentation theorycontext-dependent argumentationdefeat functionrelevance setpriorityargument attackstrategic manipulationACTIVATION-MANIPULATIONcomputational complexity
Authors
Albert Sadowski, Jarosław A. Chudziak
Abstract
The same arguments often need to be evaluated under different external regimes. An agent with influence over the regime has a strategic lever that standard formalisms do not directly capture. We introduce context-dependent argumentation frameworks (CDAFs), an extension of Dung's theory in which a defeat function determines, per context, which attacks succeed. A perspective-labeled specialisation derives the defeat function from a relevance set $ρ$ and a priority $π$. The relevance set is the agent's action space. In a small worked example, the agent's target argument is rejected under every full-relevance injective priority, yet accepted under partial activations, one of which no VAF audience can mirror. We define the corresponding decision problem, ACTIVATION-MANIPULATION, and record baseline complexity bounds. Tight bounds and multi-agent variants are left open.