From model of trust dynamics for short-term human-robot interaction

Rapid advance of robotic technologies in the last years have opened numerous venues and great challenges in the field of robotics technology. Interacting with those advanced technologies has carried huge debates on how such interactions can be instigated to create fluent interaction between humans and robots that can last for long time (human-robot interaction). One of the crucial factors that majorly influence the level of interaction between human and robot is the level of trust. Trust is the feeling of confidence that the reliance on other partner will not yield negative or dangerous consequences. In computational psychology domains, formal models (computational models) were used to acquire deep insights of human cognitive functions and behavior patterns. Therefore, this study implements formal model of trust in human robot interaction to answer how trust can be a reason to initiate interaction between human and robot. From related literature, eighteen basic factors have been established that include; personality, physical appearances, believable behavior, behavior cues, level of automation, positive experiences, transparency, perception, long term perceive risk, short term perceive risk, reliable behavior, perceive competency, positive deception, long term positive experiences, short term trust, short term distrust, long term trust, long term distrust. Those factors provide the fundamental knowledge of developing trust in robot. A formal model was developed based on a set of differential equations. Next, Five different cases were implemented to simulate various scenarios that explain the development of trust in HRI; namely, 1) high level of trust, 2) moderate high level of trust, 3) moderate level of trust, 4) moderate low level of trust, and 5) low level of trust. The developed model was verified by using mathematical analysis (stability analysis) and automated verification (temporal trace language