EAGER: Modeling Interpretive Argument with Case Analogies and Rules in Ill-Defined Domains

在工程设计和伦理学、数学发现和法律等定义不明确的领域，问题往往有不止一个“正确”的答案。在这种情况下，决策者就如何根据过去的案例以及潜在的原则和政策来决定问题提出规则或假设；通过这个解释性论证的过程，决策者可以提出假设的例子，以便引出和检验假设的规范性、逻辑性或经验性的结果。在整合决策规则、案例类比、假设例子、潜在原则和政策时，解释性论证是一种稳健推理的范例。尽管这些问题定义不明确，但解释性论证有一个潜在的逻辑，这个项目正在计算建模。通过在从现实法律领域中提取的更复杂的论点微世界、案例家族、规则、概念、原则和政策中工作，该项目正在开发一个本体，并实现推理控制机制和论点图式，计算机程序将利用这些机制进行解释性论证。对计算模型的经验评估是比较计算机和人类辩论者的论点。这项工作对人工智能、论证理论、人工智能和法律以及基于案例的推理领域做出了贡献，从长远来看，它的目标是促进智能教学系统的发展，使学生准备好进行有效、可支持和其他理性的论点，并将人工代理设计为参与争议的人类的代理人和倡导者。

In ill-defined domains such as engineering design and ethics, mathematical discovery, and law, problems often have more than one 'right' answer. In such situations decision-makers propose rules or hypotheses about how to decide the problem in light of past cases and underlying principles and policies; through this process of interpretive argument decision-makers may then pose hypothetical examples in order to draw out and test the normative, logical, or empirical consequences of the hypothesis. In integrating decision rules, case analogies, hypothetical examples, underlying principles, and policies, interpretive argument is a paradigm of robust reasoning. Although the problems are ill-defined, interpretive argument has an underlying logic, which this project is modeling computationally. By working in successively more complex argument microworlds, families of cases, rules, concepts, principles and policies drawn from realistic legal domains, the project is developing an ontology and implementing inference control mechanisms and argument schema with which a computer program will engage in interpretive argument. Empirical evaluation of the computational model is comparing arguments by the computer and by human arguers.The work contributes to the fields of AI, argumentation theory, AI and Law, and case-based reasoning, and it aims in the longer term to contribute to intelligent tutoring systems that will prepare students for making effective, supportable and otherwise rational arguments, and to design artificial agents as proxies and advocates for humans engaged in disputes.