| HYBRID STRATIFIED ATMS AND ANN FOR CASE-BASED REASONING |
| |
| 作者姓名： | 杨杰 黄欣 陆正刚 |
| |
| 摘 要： | ＩｎｔｒｏｄｕｃｔｉｏｎＭａｋｉｎｇｕｓｅｏｆｅｘｐｅｒｔｅｘｐｅｒｉｅｎｃｅｆｏｒｐｒｏｂｌｅｍｓｏｌｖｉｎｇｉｓｔｈｅｋｅｒｎｅｌｏｆＡｒｔｉｆｉｃｉａｌＩｎｔｅｌｉｇｅｎｃｅ．Ｅｘｐｅｒｔｅｘｐｅｒｉｅｎｃｅｓｏｍｅｔｉｍｅｓｉｓｄｉｆｉｃｕｌ...
|
HYBRID STRATIFIED ATMS AND ANN FOR CASE BASED REASONING |
| |
| YANG Jie,HUANG
Xin.HYBRID STRATIFIED ATMS AND ANN FOR CASE-BASED REASONING[J].Journal of Shanghai Jiaotong university,1999(1). |
| |
| Authors: | YANG Jie HUANG
Xin |
| |
| Abstract: | Case Based Reasoning (CBR) is a powerful problem
solving technique in AI, but the traditional CBR techniques have its limitations. We hybridized
stratified ATMS and ANN for CBR which can deal with case representation, case retrieving, case
adapting, learning from failure more effectively. The structure of our CBR system and
algorithms of case base reasoning in our CBR system were presented. |
| |
| Keywords: | case based reasoning (CBR) stratified assumption based truth maintenance system (ATMS) artificial neural network (ANN) |
|
