  One way to improve the relationship between humans and anthropomorphic agents
is to have humans empathize with the agents. In this study, we focused on a
task between an agent and a human in which the agent makes a mistake. To
investigate significant factors for designing a robotic agent that can promote
humans empathy, we experimentally examined the hypothesis that agent reaction
and human's preference affect human empathy and acceptance of the agent's
mistakes. The experiment consisted of a four-condition, three-factor mixed
design with agent reaction, selected agent's body color for human's preference,
and pre- and post-task as factors. The results showed that agent reaction and
human's preference did not affect empathy toward the agent but did allow the
agent to make mistakes. It was also shown that empathy for the agent decreased
when the agent made a mistake on the task. The results of this study provide a
way to control impressions of the robotic virtual agent's behaviors, which are
increasingly used in society.

Human-Computer Interaction