Regret Minimization in Games with Incomplete Information


Extensive games are a powerful model of multiagent decision-making scenarios<lb>with incomplete information. Finding a Nash equilibrium for very large instances<lb>of these games has received a great deal of recent attention. In this paper, we<lb>describe a new technique for solving large games based on regret minimization.<lb>In particular, we introduce… (More)

3 Figures and Tables


  • Presentations referencing similar topics