An Adaptive Robot Motivational System

We present a robot motivational system design framework. The framework represents the underlying (possibly conflicting) goals of the robot as a set of drives, while ensuring comparable drive levels and providing a mechanism for drive priority adaptation during the robot’s lifetime. The resulting drive reward signals are compatible with existing reinforcement learning methods for balancing multiple reward functions. We illustrate the framework with an experiment that demonstrates some of its benefits.