Autonomous System Learns Symbolic Representations from Evolving Experiences

This work presents a new architecture that allows an autonomous agent to continuously update its set of low-level capabilities and their corresponding abstract symbolic representations, enabling it to plan sequences of actions to reach more complex goals.