A Proposal for Continuous Evaluation-based Interactive Evolutionary Computation

Abstract

Interactive Evolutionary Computation (IEC) is known as an efficient method which reflects user’s subjective preference on media contents. However, user’s fatigue caused by repetitive evaluation tasks remains as a severe problem in IEC. The purpose of this study is to propose a new framework of IEC, continuous evaluation-based IEC (CEIEC) that continues user’s evaluation tasks in many days. CEIEC allows the user’s subjective evaluation day by day to have many evaluation times without severe fatigue, while conventional IECs performed user’s task in one time in one day. This study also performed a listening experiment for investigating efficiencies of CEIEC. The target of search with CEIEC was to design a bright sign sound. Sixteen subjects participated in the listening experiment which is composed of tasks of three days: in the 1st and the 2nd days, the subjects performed a selection task throughout fifteen generations. Successive update of the solution was observed during these two days. In the 3rd day, the subjects evaluated three sign sounds with 7-point scale. These three sounds were picked up from the 0th, 14th, and 29th generations, respectively. The sound with the highest score was found in the 29th generation. These results show the efficiencies of CEIEC.