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Epistemic graphs for representing and reasoning with positive and negative influences of arguments

机译:用论证的正负影响来表示和推理的认知图

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This paper introduces epistemic graphs as a generalization of the epistemic approach to probabilistic argumentation. In these graphs, an argument can be believed or disbelieved up to a given degree, thus providing a more fine-grained alternative to the standard Dung's approaches when it comes to determining the status of a given argument Furthermore, the flexibility of the epistemic approach allows us to both model the rationale behind the existing semantics as well as completely deviate from them when required. Epistemic graphs can model both attack and support as well as relations that are neither support nor attack. The way other arguments influence a given argument is expressed by the epistemic constraints that can restrict the belief we have in an argument with a varying degree of specificity. The fact that we can specify the rules under which arguments should be evaluated and we can include constraints between unrelated arguments permits the framework to be more context-sensitive. It also allows for better modelling of imperfect agents, which can be important in multi-agent applications.
机译:本文介绍了认知图,作为对概率论证的认知方法的概括。在这些图中,可以在一定程度上相信或不相信某个论点,从而在确定给定论点的状态时提供了一种更精确的替代Dung方法的方法。此外,认识论方法的灵活性允许我们既要对现有语义背后的原理进行建模,又在需要时完全偏离它们。认知图可以对攻击和支持以及既不是支持也不是攻击的关系进行建模。认识论约束表达了其他论据对给定论据的影响方式,这些认识论约束可以以不同程度的特异性限制我们对一个论据的信念。我们可以指定评估参数所依据的规则,并且可以在不相关的参数之间加入约束,这一事实使该框架对上下文更加敏感。它还可以对不完善的代理进行更好的建模,这在多代理应用中可能很重要。

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