Interactive Evolutionary Computation Creating Congruent Media Content Composed of Different Media Types

We use multiple media content every day, and using congruent media content composed of different media types is ideal for users. However, it is still difficult to obtain congruent media content. Interactive Evolutionary Computation (IEC) is a well-known method for obtaining good media content suited to each user's feelings as solutions to search problems. Conventional IECs were used for searching sole media type. This study proposes a new IEC that searches the congruent media content as a good combination of different types of media content. In the proposed IEC, the solution candidate contains variables corresponding to different media types. A system was constructed with a genetic algorithm, and it was used to investigate the efficiencies of the pro-posed IEC in the experiment. The target of creation was a relaxing set of music melody and scent. Twenty participants evaluated sets of music melodies and scents throughout ten generations in the search experiment. The experimental results showed a significant increase in the mean fitness and a significant decrease in the distance between solutions. No significant increase was observed in the maximum fitness values.