Inherent Value Systems for Autonomous Mental Development

The inherent value system of a developmental agent enables autonomous mental development to take place right after the agent’s “birth.” Biologically, it is not clear what basic components constitute a value system. In the computational model introduced here, we propose that inherent value systems should have at least three basic components: punishment, reward and novelty with decreasing weights from the first component to the last. Punishments and rewards are temporally sparse but novelty is temporally dense. We present a biologically inspired computational architecture that guides development of sensorimotor skills through real-time interactions with the environments, driven by an inborn value system. The inherent value system has been successfully tested on an artificial agent in a simulation environment and a robot in the real world.