Diagnosis in systems based on an informed tree search strategy: application to cartographic generalisation

Many real world problems can be expressed as optimisation problems. Solving such problems means to find, among all possible solutions, the one that maximises an evaluation function. One approach to solve it is to use an informed search strategy. The principle of this kind of strategy is to use problem-specific knowledge beyond the definition of the problem itself to find solutions more efficiently than with an uninformed strategy. This strategy demands to define problem-specific knowledge (heuristics). The efficiency and the effectiveness of systems based on such strategies directly depend on the utilised knowledge quality. Unfortunately, acquiring and maintaining such knowledge can be fastidious. The objective of the work presented in this paper is to propose an automatic knowledge quality diagnosis approach for systems based on an informed tree search strategy. Our approach consists in analysing the system's execution logs and in using multi-criteria decision making techniques in order to determine if the knowledge needs to be revised. We present an experiment we carried out in an industrial application domain where informed search strategies are often used: cartographic generalisation.