Paper ID: 2209.14010

Argumentative Reward Learning: Reasoning About Human Preferences

Francis Rhys Ward, Francesco Belardinelli, Francesca Toni

We define a novel neuro-symbolic framework, argumentative reward learning, which combines preference-based argumentation with existing approaches to reinforcement learning from human feedback. Our method improves prior work by generalising human preferences, reducing the burden on the user and increasing the robustness of the reward model. We demonstrate this with a number of experiments.

Submitted: Sep 28, 2022