Training for Implicit Norms in Deep Reinforcement Learning Agents through Adversarial Multi-Objective Reward Optimization

We propose a deep reinforcement learning algorithm that employs an adversarial training strategy for adhering to implicit human norms alongside optimizing for a narrow goal objective. Previous methods which incorporate human values into reinforcement learning algorithms either scale poorly or assume hand-crafted state features. Our algorithm...