Why Should You Care? An Arousal-Based Model of Exploratory Behavior for Autonomous Robots

The question of how autonomous robots could be part of our everyday life is of a growing interest. We present here an experiment in which an autonomous robot explores its environment and tries to familiarize itself with the features available using a neural-network-based architecture. The lack of stability of its learning structures increases the arousal level of the robot, pushing the robot to look for comfort from its caretaker to reduce the arousal. In this paper, we studied how the behavior of the caretaker influences the course of the robot exploration and learning experience by providing certain amount of comfort during this exploration. We then draw some conclusions on how to use this architecture together with related work, to enhance the adaptability of autonomous robots development.