相同的论点常常需要在不同的外部制度下进行评估。对政权有影响力的代理人拥有标准形式主义无法直接抓住的战略杠杆。我们引入上下文相关的论证框架(CDAFs),，它是Dung的理论的扩展，其中失败函数确定每个上下文,攻击是否成功。被阻止的攻击被反转而不是被删除,，因此扩展在攻击关系方面保持无冲突。视角标记的专业化从相关性集 $\rho$ 和优先级 $\pi$ 导出失败函数。相关性集是代理的 的操作空间。在一个小型工作示例,中，代理'的目标参数在每个完全相关优先级,下被拒绝，但在部分激活下被接受，其结果没有VAF受众可以反映。我们定义相应的决策问题, ACTIVATION-MANIPULATION, 并记录基线复杂性界限。对于具有强制视角的扎根语义，问题是 NP 完全,，困难来自激活选择本身。
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的 theory in which a defeat function determines, per context, which attacks succeed. Blocked attacks are inverted rather than deleted, so extensions stay conflict-free with respect to the attack relation. A perspective-labeled specialisation derives the defeat function from a relevance set $\rho$ and a priority $\pi$. The relevance set is the agent的 action space. In a small worked example, the agent的 target argument is rejected under every full-relevance priority, yet accepted under a partial activation whose outcome no VAF audience can mirror. We define the corresponding decision problem, ACTIVATION-MANIPULATION, and record baseline complexity bounds. For grounded semantics with mandatory perspectives the problem is NP-complete, and the hardness comes from the activation choice itself.
科目:人工智能(cs.AI)
Subjects: Artificial Intelligence (cs.AI)