Various cognitive and computational models have addressed the use of previous experience to understand a new domain. In particular, research in case-based reasoning has explored the ideas of retrieving and adapting previous experience in the form of cases. If the cases take the form of plans, the process is referred to as case-based planning. We have developed a computational model of Exploratory Discovery which integrates case-based reasoning and case-based planning. Motivated by results from cognitive science, we incorporated into this model features for improving the learning process such as exploration and self-questioning. This paper will focus on the index vocabulary needed to accomplish the interaction between the generation of self-questions and the experimentation process. This interaction depends on questions asked, answers given, and previously performed experiments; interaction is therefore situated.
|Title of host publication||Progress in Case-Based Reasoning|
|Subtitle of host publication||Proceedings of First United Kingdom Case-Based Reasoning Workshop|
|Editors||Ian D Watson|
|Publication status||Published - 1996|
|Name||Lecture Notes in Computer Science|
- case-based reasoning