|
Abstract : |
Given an arbitrary learning situation, it is difficult to determine the most appropriate learning strategy. The goal of this research is to provide a general representation and processing framework for introspective reasoning for strategy selection. The learning framework for an introspective system is to perform some reasoning task. As it does, the system also records a trace of the reasoning itself, along with the results of such reasoning. If a reasoning failure occurs, the system retrieves and applies an introspective explanation of the failure in order to understand the error and repair the knowledge base. A knowledge structure called a Meta-Explanation Pattern is used to, |