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.

翻译：相同论证常需在不同外部机制下评估。对机制具有影响力的主体拥有标准形式化方法无法直接捕捉的策略杠杆。我们引入语境依赖论证框架（CDAFs），这是对Dung理论的扩展，其中失效函数根据具体语境决定哪些攻击成立。视角标记特化方法通过相关性集合ρ和优先级π推导失效函数，其中相关性集合是主体的行动空间。在一个小型实例中，主体的目标论证在所有全相关内射优先级下均被拒绝，却在部分激活下被接受——其中一种激活模式是任何VAF听众都无法复现的。我们定义了相应的决策问题ACTIVATION-MANIPULATION，并记录了基础复杂性边界。紧界与多主体变体仍为开放问题。