Paul Barde

Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic

2020 · arXiv (Cornell University)

Multi-agent adversarial inverse reinforcement learning (MA-AIRL) is a recent approach that applies single-agent AIRL to multi-agent problems where we seek to recover both policies for our agents and reward functions that promote expert-like behavior. While …