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Helping a CBR Program Know What It Knows

机译:帮助CBR程序了解其所知

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Case-based reasoning systems need to know the limitations of their expertise. Having found the known source cases most relevant to a target problem, they must assess whether those cases are similar enough to the problem to warrant venturing advice. In experimenting with SIROCCO, a two-stage case-based retrieval program that uses structural mapping to analyze and provide advice on engineering ethics cases, we concluded that it would sometimes be better for the program to admit that it lacks the knowledge to suggest relevant codes and past source cases. We identified and encoded three strategic metarules to help it decide. The metarules leverage incrementally deeper knowledge about SIROCCO's matching algorithm to help the program "know what it knows." Experiments demonstrate that the metarules can improve the program's overall advice-giving performance.
机译:基于案例的推理系统需要了解其专业知识的局限性。在找到与目标问题最相关的已知源案例之后,他们必须评估这些案例是否与该问题足够相似以提供风险建议。在SIROCCO的试验中,这是一个基于案例的两阶段检索程序,该程序使用结构映射来分析工程伦理案件并提供相关建议,我们得出结论,有时该程序承认它缺乏建议相关代码的知识有时会更好和过去的原始案例。我们确定并编码了三个战略性元规则以帮助其做出决定。这些元规则利用有关SIROCCO匹配算法的越来越深的知识来帮助程序“知道它所知道的”。实验表明,这些规则可以提高程序的整体建议性能。

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