To explore the social applications of reinforcement learning, research and development of AI capable of playing games that simulate the complexity of the real world is beneficial. However, ...opportunities to learn from such complex games are rare. We have developed an AI learning interface for a widely played video game that possesses a considerable complexity. To demonstrate the feasibility of reinforcement learning through this interface, we have developed AI which can play the game with reinforcement learning, and the result indicate that the AI can handle the game's complexity. Furthermore, this effort showed the potential to bridge AI and the general public.
The presentation of a moving tactile stimulus to a person's forearm evokes a pleasant sensation. The speed, intensity, and contact area of the strokes should be systematically changed to evaluate the ...relationship between pleasantness and tactile stimuli in more detail. Studies have examined the relationship between stroking stimulation and pleasant sensations using airborne ultrasound tactile displays. The ultrasound-based method has the advantage of reproducible control of the speed, intensity, and contact area of the stimulus. In this study, we prepared new stimuli focusing on the modulation methods and the contact area and aimed to clarify their relationship with pleasantness in more detail. Evaluating subjective sensations, such as pleasantness, numerically and consistently is challenging, warranting evaluation based on comparison. We propose a stimulus evaluation method that combines rough evaluation using Likert scales, detailed evaluation using pairwise comparisons, and quantification of comparison data using the Bradley--Terry model. As a result, we confirmed that the stimulus using lateral modulation and that with a large contact area used in this study were more pleasant than the conventional stimulus for six out of ten participants.
To aim at the realization of a helical fusion reactor, we study multi-objective optimization of coil shapes, which satisfy various requirements. In the magnetic field configuration created by these ...coils, several unfavorable examples are found: some of them have magnetic islands or doublet configurations. In order to automatically and quickly exclude such cases that hinder the optimization, we have developed a new method to detect unfavorable magnetic surfaces by using image recognition. Binarization and erosion are performed as preprocessing, and then blanks of magnetic islands and doublets are extracted as recognition targets. Consequently, we have developed a classifier with high performance. Using this trained classifier, we have shown that almost all cases with unfavorable magnetic surfaces in various magnetic configurations can be excluded in a short time and with high precision.
