Multi-Agent Inverse Q-Learning from Demonstrations

Nathaniel Haynam, Adam Khoja, Dhruv Kumar +2

When reward functions are hand-designed, deep reinforcement learning algorithms often suffer from reward misspecification, causing them to learn suboptimal policies in terms of the…