Learning with whom to communicate using relational reinforcement learning

Relational reinforcement learning (RRL) has emerged in the machine learning community as a new promising subfield of reinforcement learning (RL) (e.g. [1]). It upgrades RL techniques by using relational representations for states, actions and learned value-functions or policies to allow more natural representations and abstractions of complex tasks. This leads to a serious state space reduction, allowing to better generalize and infer new knowledge.