Friend-or-Foe Q-learning in General-Sum Games
Michael L. Littman · 2001
This paper describes an approach to rein-forcement learning in multiagent general-sum games in which a learner is told to treat each other agent as either a \\friend " or \\foe". This Q-learning-style algorithm provides strong convergence guarantees compared to an ex-isting Nash-equilibrium-based learning rule.