online mirror descent algorithm

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Zhengyuan Zhou — Multi-Agent Online Learning with Imperfect Information

George B. Dantzig Auditorium - 1174 Etcheverry Hall Etcheverry Hall, Berkeley

Abstract: We consider a model of multi-agent online learning under imperfect information, where the reward structures of agents are given by a general continuous game. After introducing a general equilibrium stability notion for continuous games, called variational stability, we examine the well-known online mirror descent (OMD) learning algorithm (a broad family of no-regret online learning…

Zhengyuan Zhou — Multi-Agent Online Learning with Imperfect Information

George B. Dantzig Auditorium - 1174 Etcheverry Hall Etcheverry Hall, Berkeley

Abstract: We consider a model of multi-agent online learning under imperfect information, where the reward structures of agents are given by a general continuous game. After introducing a general equilibrium stability notion for continuous games, called variational stability, we examine the well-known online mirror descent (OMD) learning algorithm (a broad family of no-regret online learning…