分歧并承诺：基于论证的一致程度
Disagree and Commit: Degrees of Argumentation-based Agreements
AI总结：
本文面向自主智能体的部分承诺问题，基于抽象论证与基于价值的论证提出一致场景、满足度及多类一致度，并分析新信息扩展对其可靠性的影响。
摘要：
在合作性人类决策中，一致往往不是完全的；只要人们在一定程度上确信，在没有剧烈意外变化的情况下，相关各方未来很可能会信守承诺，那么部分程度的一致就足以承诺某项决策并继续推进。本文引入“一致场景”的概念，使人工自主智能体能够利用论证的形式化模型，尤其是抽象论证和基于价值的论证，达成此类一致。我们引入满足度以及（最小值、均值和中位数）一致度的概念，并提出一种度量，用于衡量基于价值的论证框架中的某个价值对这些概念的影响。随后，我们分析当一致场景因新信息而扩展时，一致程度会如何受到影响，以揭示动态场景中部分一致的可靠性。所引入概念的实现作为基于论证的推理软件库的一部分予以提供。
英文摘要：
In cooperative human decision-making, agreements are often not total; a partial degree of agreement is sufficient to commit to a decision and move on, as long as one is somewhat confident that the involved parties are likely to stand by their commitment in the future, given no drastic unexpected changes. In this paper, we introduce the notion of agreement scenarios that allow artificial autonomous agents to reach such agreements, using formal models of argumentation, in particular abstract argumentation and value-based argumentation. We introduce the notions of degrees of satisfaction and (minimum, mean, and median) agreement, as well as a measure of the impact a value in a value-based argumentation framework has on these notions. We then analyze how degrees of agreement are affected when agreement scenarios are expanded with new information, to shed light on the reliability of partial agreements in dynamic scenarios. An implementation of the introduced concepts is provided as part of an argumentation-based reasoning software library.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
