打了一辈子德州,居然输给了新手AI!(下篇)

打了一辈子德州,居然输给了新手AI!(上篇):https://www.moshike.com/a/347.html
此时,对B而言,就是一个不完美博弈,他无法从A选择play从而判断A手中的硬币是正面还是反面。
这时有两个极限情况,如果B总是猜正面,那么聪明的A就会变化策略,当他抛到正面时就卖掉硬币,如果抛到反面才玩游戏,这样B必然会输。此时,A的期望分数为
0.5(抛到正面的概率)*0.5(选择sell的得分)+0.5(抛到反面的概率)*1(选择play的得分)=0.75
如果B总是猜反面,那么A抛到正面时就会选择play,得一元;抛到反面就会选择sell卖掉硬币,这样只赔五毛钱。所以A的期望是
0.5(抛到正面的概率)*1(选择play的得分)+0.5(抛到反面的概率)*(-0.5)(选择sell的得分)=0.25
此时,出现一个知识点,叫纳什均衡,也就是B为了有效的降低损失,他最有效的策略就是以0.25的概率猜正面,以0.75的概率猜反面,这样可以确保他的胜算最大。
而博弈永远是一个动态的过程,如果B持续按照固有的策略做决策,那么A也会根据B的决策结果调整自己的策略。所以,对B最安全的方法,就是不断更新A卖掉硬币会得到的回报,持续寻找最优解。
我们聪明的计算机就是通过这样的方法动态的计算牌友们押注所带来的回报期望,进而“持续更新对手的套路”,最终获得了「比赛过程中,人类选手整体上从未领先过」的效果。
看来,想要和AI斗智,人类的小脑筋maybe还需要转的更快才行嘞,也许没有套路才是最大的套路哦。
都说金融大佬都爱玩德州,看完这篇文章,金融大佬们是否有些启发呢?
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