This project forked from thuxugang/doudizhu
AI斗地主
deecamp斗地主
提供了可以结合AI的程序引擎，在next_moves中提供按照规则的出牌所有可能性，需要自己实现从next_moves中选择所出的牌（myutil中的choose方法），默认random
1.页面展示，提供可视化调试方法
2.可以选择跟人对战
模仿OpenAI，提供了可以结合RL的程序引擎，可以选择对手为random或陈潇规则(cxgz)或自身(self)，但是训练时只能训练一个且为player 1。该分支rl模型为prioritized_dqn，具体模型参考https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow 。
目前胜率 vs random（90%）， cxgz（44%）
模仿OpenAI，提供了可以结合RL的程序引擎，可以同时训练多个rl player
mcts暴力解决（TODO：由于deepcopy牌局的回复速度比较慢，1000/6s）
Deecamp第五组
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