An experiment in agent teaching by subject matter experts

被引:8
|
作者
Tecuci, G [1 ]
Boicu, M [1 ]
Bowman, M [1 ]
Marcu, D [1 ]
Shyr, P [1 ]
Cascaval, C [1 ]
机构
[1] George Mason Univ, Learning Agents Lab, Fairfax, VA 22030 USA
关键词
instructable agents; knowledge acquisition; machine learning; course of action critiquing; experimentation;
D O I
10.1006/ijhc.2000.0401
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a successful knowledge-acquisition experiment in which subject matter experts who did not have any prior knowledge-engineering experience succeeded in teaching the Disciple-COA agent how to critique courses of action, a challenge problem addressed by the DARPA's High-Performance Knowledge Bases program. We first present the COA challenge problem and the architecture of Disciple-COA, a learning agent shell from the Disciple family. Then we present the knowledge acquisition experiment, detailing both the expert-Disciple interactions, and the automatic knowledge base development processes that take place as a result of these interactions. The results of this experiment provide strong evidence that the Disciple approach is a viable solution to the knowledge acquisition bottleneck. (C) 2000 Academic Press.
引用
收藏
页码:583 / 610
页数:28
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