Remembering to Add: Competence-preserving Case-Addition Policies for Case Base Maintenance

Case base maintenance is gaining increasing recognition in research and the practical ap plications of case based reasoning CBR This intense interest is highlighted by Smyth and Keane s research on case deletion policies In their work Smyth and Keane advocated a case deletion policy whereby the cases in a case base are classi ed and deleted based on their cover age potential and adaptation power The al gorithm was empirically shown to improve the competence of a CBR system and outperform a number of previous deletion based strategies In this paper we present a di erent case base maintenance policy that is based on case addi tion rather than deletion The advantage of our algorithm is that we can place a lower bound on the competence of the resulting case base we demonstrate that the coverage of the com puted case base cannot be worse than the op timal case base in coverage by a xed lower bound and the coverage is often much closer to optimum We also show that the Smyth and Keane s deletion based policy cannot guarantee any such lower bound Our result highlights the importance of nding the right case base maintenance algorithm in order to guarantee the best case base coverage We demonstrate the e ectiveness of our algorithm through an experiment in case based planning