IGAのための心理的尺度に基づいたファジィ推論による適合度割当て法(<論文特集>対話型進化計算法)

抄録

Interactive genetic algorithm(IGA) has been recognized as a useful tool for searching problems were fitness is determined by human intervention. It has an important aspect as a user-interface when searching for a target according to user's subjective factors such as similarity, attractiveness, preference, and so forth. Two important problems of the IGA are how to assign fitness to populatiions utilizing the human sense, and how to reduce the user's load. We compared three fitness assignment methods, "rating all", "bias", and "fuzzy" in searching for a cartoon which has been imagined by user. The latter two methods have been proposed by us. The user's load was lighter and time to process was shorter in the fuzzy method compared with the rating all method. However, the final populations in the fuzzy method did not become as similar to a target as in the rating all method. This is because the fittest cartoon face is picked up based on a psychometrical measure, while fitness of the other cartoon faces is calculated with a physical measure in the fuzzy method, that is, the fuzzy reasoning is performed in the physical face space. In this paper we improved the fuzzy method by mapping the cartoon faces from the face space to the psychometrical space and performing the fuzzy reasoning in the psychometrical space. The distance between any two faces in the psychometrical space expresses the correct similarity between them. Therefore the fitness of the other faces as well as the picked-up one can be obtained based on the human sense. Finally the fuzzy method can get the advantage of the rating all method, that is coming closest to a target, without sacrificing its own advantages, those are user-friendliness and quickness.