从分类求解问题到约束求解范式(医学计算)

Proceedings of the International Workshop on Artificial Intelligence for Industrial Applications Pub Date : 1988-05-25 DOI:10.1109/AIIA.1988.13335

F. Mizoguchi

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引用次数: 0

摘要

本文研究了知识系统中约束求解问题的三种方法:(1)开发了用于定性仿真的领域相关约束求解器，在逻辑规划中实现了Kuiper算法;(2)将Prolog统一扩展到不等式和实算术领域，建立了一般约束求解器;(3)使用承诺选择的不确定性语言，如Prolog、CP和GHC作为并发约束语言。医学诊断的知识获取被视为一个示例应用。

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From classification solving problem to constraint solving paradigm (medical computing)

Three approaches to the constraint-solving problem in knowledge systems are examined: (1) the development of a domain-dependent constraint solver for qualitative simulation, implementing Kuiper's algorithm in logic programming; (2) the building of a general constraint solver by extending Prolog unification into the inequality and real arithmetic domain; and (3) the use of committed choice nondeterministic languages such as Prolog, CP, and GHC for a concurrent constraint language. Knowledge acquisition for medical diagnostics is considered as an example application.<>

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Proceedings of the International Workshop on Artificial Intelligence for Industrial Applications

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