An Optimal Case-Base Maintenance Method for Compositional Adaptation Applications

Abstract

Case-base maintenance method aims at maintaining a compressed case-base which is useful for solving future problems effectively. In this paper, we propose an optimization formulation to arrive at a compressed case-base that can find a solution for the rest of the cases in the case-base that involves compositional adaptation process. The objective of the optimization problem is to minimize the footprint set size and maximize the quality of solutions that can be adapted from the footprint set. We empirically studied the proposed formulation on four different datasets and the results show that the proposed model is effective and overcomes the limitation of the existing optimal footprint method in compositional adaptation applications.