RECENT PROCESS AND PROSPECT OF MULTI-AGENT REINFORCEMENT LEARNING UNDER THE PERSPECTIVE OF COMPETITION AND COOPERATION
With the rapid development of deep learning and reinforcement learning,multi-agent reinforcement learning(MARL)has become a common approach to solve the large scale complex sequential decision-making problem.In order to promote the development of this field,this paper collects and reviews recent research results from the perspective of competition and cooperation.This paper introduced deep reinforcement learning and introduced the basic theoretical framework of MARL-Markov game and extensive game,and especially emphasized the reinforcement learning algorithms developed recently in three scenarios of competition,cooperation and mixture.This paper discussed the core challenge of MARL that was non-stationary of the environment,and an example was given to summarize and prospect its solutions.
Deep learningReinforcement learningMulti-agent reinforcement learningNon-stationary of the environment
国家科技期刊平台
NSTL
万方数据
维普
