CABOT: an adaptive approach to case-based search

This paper describes CABOT, a case-based system that is able to adjust its retrieval and adaptation metrics, in addition to storing cases. It has been applied to the game of OTHELLO. Experiments show that CABOT saves about half as many cases as similar systems that do not adjust their retrieval and adaptation mechanisms. It also consistently beats these systems. These results suggest that existing case-based systems could save fewer cases without reducing their current levels of performance. They also demonstrate that it is beneficial to distinguish failures due to missing information, faulty retrieval, and faulty adaptation.