Issue spotting in a system for searching interpretation spaces
Issue spotting in a system for searching interpretation spaces
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搜索解释空间系统中的问题发现
DOI：
10.1145/74014.74035
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发表时间：
1989
期刊：
影响因子：
--
通讯作者：
T. Gordon
中科院分区：
文献类型：
--
作者：
T. Gordon
描述了一种发现问题的方法，该方法使用我们正在开发的用于搜索解释空间和构建法律的论点的系统。该系统与被称为法律的实证主义的法律的哲学兼容，但不依赖于其明确案例的概念。应用于该系统的人工智能方法包括ATMS的原因维护系统，普尔的默认推理框架，和一个交互式的自然演绎定理证明与可编程控制组件，包括领域相关的启发式知识。我们的问题发现的方法相比，加德纳的程序，以确定提供和接受法学院考试问题提出的困难和容易的问题。
A method for spotting issues is described which uses a system we are developing for searching interpretations spaces and constructing legal arguments. The system is compatible with the legal philosophy known as legal positivism, but does not depend on its notion of clear cases. AI methods applied in the system include an ATMS reason maintenance system, Poole's framework for default reasoning, and an interactive natural deduction theorem prover with a programmable control component for including domain-dependent heuristic knowledge. Our issue spotting method is compared with Gardner's program for identifying the hard and easy issues raised by offer and acceptance law school examination questions.