Intelligent system of selecting key search algorithms automatically

This paper proposes an automatic selection method for key search algorithms. The methodology has been implemented in a system called KESE2. Key search algorithms are selected according to user's requirements through conversation controlled by inferences performed upon an evaluation table. The evaluation table has values representing fitness between search algorithms and their characteristics, or properties, to the applications. The selection algorithm presented determines candidates of key search algorithms by reducing unsuitable methods step by step. The questions to be asked to the user are driven by inferences over the restricted set. The paper also proposes an assisting facility that consists of both a supporting function and a program synthesis function. Experimental results show that by using the selection algorithm, the number of questions to be asked in order to select the appropriate key search algorithm was less than half the number of questions without inferences.