| 一种在非单调和不完全领域知识下的EBL方法 |
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| 引用本文： | 杨杰,施鹏飞.一种在非单调和不完全领域知识下的EBL方法[J].上海交通大学学报,1996,30(1):117-121,134. |
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| 作者姓名： | 杨杰 施鹏飞 |
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| 摘 要： | 基于解释的学习（ＥＢＬ）克服了基于相似性的学习中的一些局限性，但是由于领域知识的不完全性和非单调法，在ＥＢＬ过程中会出现等多重解释问题，运用分层ＡＴＭＳ（基于解释的真值维护系统）来实现ＥＢＬ方法，由于分民支ＡＴＭＳ能处理非单调推理和多重假设集，因而它能根据不同原因解决了ＥＢＬ中的多重解释问题。
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| 关 键 词： | 人工智能 多重解释问题 机器学习 EBL法 |
An EBL Method under Nonmonotonic and Incomplete Domain Knowledge |
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| Yang Jie, Shi Pengfei.An EBL Method under Nonmonotonic and Incomplete Domain Knowledge[J].Journal of Shanghai Jiaotong University,1996,30(1):117-121,134. |
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| Authors: | Yang Jie Shi Pengfei |
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| Abstract: | Explanation-based Learning can overcome some limitations in similarity-based learning. But due to the nonmonotonic or incomplete domain theories, multiple explanation problems may arise in EBL. This paper presents an approach by using stratified ATMS to realize EBL. Because stratified ATMS can deal with nonmonotonic reasoning and multiple assumption sets, it can solve multiple explanation problems in EBL according to different reasons. |
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| Keywords: | artificial intelligence explanation-based learning similarity-based leraning multiple explanation problem stratified ATMS |
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