Survey of Multi-agent Reinforcement Learning in Markov Games
Guoyin Zhang · Kongzhi yu juece · 2005
The research on multi-agent reinforcement learning is to deal with the problem of play skill between agents,just with the concept of stochastic game.All the things of the success of single agent reinforcement learning,the mathematics basis of the game theory,and the potential applications in complex task environment make the multi-agent learning an important topic in the field of machine learning.The formal definition of basic concepts in stochastic game is given first,and then the algorithms of learning in stochastic game and repeated game are introduced.Last,the research on the applications of multi-agent learning is summarized,and the problems remaining unsolved together with the future work are concluded.