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一种CBR与RBR相结合的快速预案生成系统

ISSN号：1000-1239
期刊名称：《计算机研究与发展》
时间：0
分类：TP18[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]
作者机构：[1]中国科学院计算技术研究所智能信息处理重点实验室,北京100080, [2]中国科学院研究生院,北京100049
相关基金：国家自然科学基金项目（60435010,90604017,60675010）;国家“八六三”高技术研究发展计划基金项目（2006AA012128）;国家“九七三”重点基础研究发展规划基金项目（2003CB317004）;北京市自然科学基金项目（4052025）

关键词：规则推理, 范例推理, 紧急事件, 决策支持, 相似度, 主体, case based reasoning, rule based reasoning, emergency, decision support, similarity, agent

中文摘要：

将范例推理（case based reasoning,CBR）与规则推理（rule based reasoning,RBR）两种人工智能技术相结合,实现一种快速预案生成系统.它有效地解决了单纯RBR系统在预案生成过程中的时间延迟缺陷和知识库难以获取的瓶颈.通过CBR工具,能够把以前发生的紧急事件和解决方案生成预案.一旦新的事件发生,首先从预案库中进行案例的相似性检索,如果没有检索到预案或者检索到的预案匹配度很低,再采用RBR系统对紧急事件进行规则推理,然后把推理结果重新存入预案库.实验数据表明,这种方法对单纯RBR系统在时间响应上进行了有效的优化.另外,因为案例的获取比专家系统推理规则的获取容易得多,它同时解决了RBR系统推理规则难以获取的瓶颈.根据这种思想,实现了CBR与RBR结合的快速预案生成系统.目前,它已经应用到抗洪抢险的预案生成和城市应急联动的决策支持上,效果表明它在预案生成速度以及实际可操作性上都具有明显优势.

英文摘要：

It is important to generate response plan to deal with the emergency, which will greatly decrease the cost. The traditional method is using the expert system （rule based reasoning system） to generate the decision method. However, this approach is often slow and it is also hard to generate the reasoning rules sometimes. This paper combines two kinds of artificial intelligence techniques, case based reasoning （CBR） and rule based reasoning （RBR）, to construct a quick emergency response plan generation system. It improves the performance and solves the knowledge acquisition bottleneck of traditional RBR systems. With the CBR tool CbrSys, decision support is generated from the previous emergency cases and solutions in database through the similarity retrieval. Once new emergency events happen, the case base is first retrieved to find the similar solutions. Only when the solution cases can not be obtained from the case base or the case solutions are not satisfactory, the RBR system is used to reason for solution and then the reasoning result is stored in the case base for future use. A series experiments are conducted to test its efficiency, which shows that it is superior to the traditional RBR system in response speed. The system is now applied in flood decision support system and city emergency inter-act project.

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