<i>Q</i>learning in the minority game

Abstract

We present a numerical investigation of the minority game model, where the dynamics of the agents is described by the Q-learning algorithm. The numerical results show that the Q-learning dynamics is suppressing the "crowd effect," which is characteristic of the minority game with standard inductive dynamics, and it converges to a stationary state that is close to the optimal Nash equilibrium of the game.