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Information Revelation Strategies in Abstract Argument Frameworks Using Graph Based Reasoning

机译:基于图论的抽象论证框架中的信息启示策略

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The exchange of arguments between agents can enable the achievement of otherwise impossible goals, for example through persuading others to act in a certain way. In such a situation, the persuading argument can be seen to have a positive utility. However, arguments can also have a negative utility - uttering the argument could reveal sensitive information, or prevent the information from being used as a bargaining chip in the future. Previous work on arguing with confidential information suggested that a simple tree based search be used to identify which arguments an agent should utter in order to maximise their utility. In this paper, we analyse the problem of which arguments an agent should reveal in more detail. Our framework is constructed on top of a bipolar argument structure, from which we instantiate bonds - subsets of arguments that lead to some specific conclusions. While the general problem of identifying the maximal utility arguments is NP-complete, we give a polynomial time algorithm for identifying the maximum utility bond in situations where bond utilities are additive.
机译:代理之间的论据交换可以实现原本不可能实现的目标,例如通过说服他人以某种方式采取行动。在这种情况下,可以说服的论点具有积极作用。但是,论点也可能具有负面作用-说出论点可能会泄露敏感信息,或者将来阻止信息用作讨价还价的筹码。先前有关机密信息争论的工作表明,可以使用基于树的简单搜索来确定代理应发出哪些参数以最大化其效用。在本文中,我们分析了代理商应更详细地揭示哪些论点的问题。我们的框架是在双极论证结构的基础上构建的,从中我们可以实例化键-引出某些特定结论的论证子集。虽然确定最大效用参数的一般问题是NP完全,但我们给出了多项式时间算法来确定键效用为加性的情况下的最大效用键。

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