Inductive Logic Programming for Transparent Alignment with Multiple Moral Values

Reinforcement learning is a key paradigm for developing intelligent agents that operate in complex environments and interact with humans. However, researchers face the need to explain and interpret the decisions of these systems, especially when it comes to ensuring their alignment with societal value systems. This paper marks the initial stride in an ongoing research direction by applying an inductive logic programming methodology to explain the policy learned by an RL algorithm in the domain of autonomous driving, thus increasing the transparency of the ethical behaviour of agents.