Acceptability of Virtual Characters as a Social Skills Trainer: Usability Study (Preprint)

BACKGROUND Social skills training by human trainers is a well-established method to obtain appropriate social interaction skills and strengthen social self-efficacy. Our previous works automated social skills training by developing a virtual agent that teaches social skills through interaction. This study attempts to investigate the effect of virtual agent design on automated social skills training. However previous works have not investigated virtual agent design for virtual social skills trainers. OBJECTIVE The three main purposes of this research are summarized: to investigate virtual agent appearance for automated SST, to investigate the relationship between acceptability and other measures (likeability, acceptability, realism, and familiarity), and to investigate the relationship between likeability and an individual’s characteristics (gender, age, and autistic traits). METHODS We prepared images and videos of a virtual agent, and 1,218 crowdsourced workers rated the virtual agents through a questionnaire. In designing personalized virtual agents, we investigated the acceptability, likeability, and other impressions of the virtual agents and their relationship to the individuals’ characteristics. RESULTS As a result, we found the difference between the virtual agents in all measures (P < 0.001). A female anime-type virtual agent was rated as the most likeable. We also confirmed that participants’ gender, age, and autistic traits are related to the ratings. CONCLUSIONS We confirmed the effect of virtual agent design on automated social skills training. Our findings are important in designing the appearance of an agent for use in personalized automated social skills training.

Agent-based target evaluation and fire doctrine: an aspect-oriented programming view

Threat evaluation is a vital process for any defense system, and it consists of a series of calculation and evaluation based on the inferred capabilities and intents of the targets that aim to give damage to defended assets. Target evaluation is proceeded in a wargame and the aim is to compare weapon target pairs according to a set of criteria. The target evaluation cycle is repeated anytime a new detection is received and when any change happens in the target currently detected. The whole process consists of a set of tasks that are shared between Command and Control units and the tasks require different responsibilities. Each task is succeeded by a specific behavior that is represented as a reasonably ordered set of actions. The task sharing is organized by taking the C2 architectures into account. In this paper, an agent-based command and control entity, which is in charge of target evaluation and giving engagement decision, is designed and it is situated in an air defense simulation environment. The study aims to propose an agent design in military decision-making domain, bringing analytic methods with the first-order logic together, and combine aspect orientation with agent design. The study also improves dynamic aspect management in agent programming using the relation concept.