Performance Evaluation of Interactive Evolutionary Computation Applying Gaze Information

抄録

We present an Interactive Evolutionary Computation (IEC) system that applies user gaze information. Historically, IEC systems have faced the problem of heavy user evaluation loads. Therefore, to solve this issue, we apply a user gaze information approach to solve such issues. When user gaze information is applied to the evaluation of candidate solutions, IEC systems can obtain user evaluation information while they view multiple candidate solutions. In this paper, we verify the effectiveness of the eye tracking IEC system using evaluation experiments with real users. In the experiment, we use a normal IEC system as a comparison method where users evaluate candidate solutions by 10-stage evaluation manually. The experimental results show that the eye tracking IEC method can generate solutions that offer results equivalent to the compared system.