Systematic Experimentation with Deductive Learning: Satisficing vs. Optimizing search

Most of the research conducted in the area of deductive learning is experimental. However, many of the experiments reported are far from being systematic and thorough. There are many parameters that are embedded in the system's architecture and it is not clear how they effect the utility of the learned knowledge. In this paper we describe an attempt to perform systematic experiments in the domain of deductive learning. The part described here explores how the search strategy employed during problem solving and during learning effects the utility of learning process. It was concluded that the utility of deductive learning is negative when the learned knowledge is applied in optimizing search procedure during problem solving, but becomes positive in satisficing search. It was also concluded that for off-line learning it is more beneficial to use optimizing search during the learning process. Knowledge acquired in this method improves both the efficiency and the quality of the problem solving.