A satisficing knowledge-based system

L. Mazlack
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Abstract

A satisficing knowledge-based system reaches a satisfactory resolution as quickly as possible. The author focuses on the principles that can be used to support a methodology that will produce satisficing decisions in a data-driven knowledge-based system. A codified satisficing methodology that has been implemented is also presented. The purpose of satisficing is to resolve as few initial condition and goal states as can be managed, consistent with reaching a satisfactory answer. This is within the normal constraints of an expert system, namely that the graph resolution would appear to be 'natural' to a human user. This requires that the inference engine satisfactorily exhaust a particular topic before moving onto the next topic. Satisficing constraints, when attained, indicate that there is sufficient supporting information for a rule and that the evidence for it does not need to be further considered.<>
令人满意的以知识为基础的系统
一个令人满意的以知识为基础的系统能尽快得到满意的解决方案。作者着重于可用于支持在数据驱动的基于知识的系统中产生令人满意的决策的方法的原则。本文还介绍了一种已被实施的令人满意的编纂方法。满足的目的是解决尽可能少的初始条件和目标状态,以达到令人满意的答案。这是在专家系统的正常约束范围内,即图形分辨率对人类用户来说是“自然的”。这要求推理引擎在移动到下一个主题之前令人满意地耗尽一个特定主题。满足约束条件,当达到时,表明有足够的支持信息的规则,它的证据不需要进一步考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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