  In recent years, robotics has evolved, placing robots in social contexts, and
giving rise to Human-Robot Interaction (HRI). HRI aims to improve user
satisfaction by designing autonomous social robots with user modeling
functionalities and user-adapted interactions, storing data on people to
achieve personalized interactions. Personality, a vital factor in human
interactions, influences temperament, social preferences, and cognitive
abilities. Despite much research on personality traits influencing human-robot
interactions, little attention has been paid to the influence of the robot's
personality on the user model. Personality can influence not only temperament
and how people interact with each other but also what they remember about an
interaction or the person they interact with. A robot's personality traits
could therefore influence what it remembers about the user and thus modify the
user model and the consequent interactions. However, no studies investigating
such conditioning have been found. This paper addresses this gap by proposing
distinct user models that reflect unique robotic personalities, exploring the
interplay between individual traits, memory, and social interactions to
replicate human-like processes, providing users with more engaging and natural
experiences
