Learning with opponent-learning awareness by Foerster, J, Chen, R, Al-Shedivat, M, Whiteson, S, Abbeel, P, Mordatch, I

“…Applied to infinitely repeated matching pennies, LOLA agents converge to the Nash equilibrium. In a round robin tournament we show that LOLA agents can successfully shape the learning of a range of multi-agent learning algorithms from literature, resulting in the highest average returns on the IPD. …”