Jakob Foerster (Oxford University) presents on Learning with Opponent-Learning Awareness (LOLA), a multi-agent reinforcement learning method in which each agent shapes the anticipated learning of the other agents in the environment. Its learning rule includes a term that accounts for the impact of one agent’s policy on the anticipated parameter update of the other agents.
