Reinforcement Learning, Monte Carlo Method, Python3.
reward is the number of wining of that state. As expected, when a player has value 20 or 21, which is at the rear of the plot, one is more likely to win. In overall, this HIT20 policy gives us 30.6% of wining, 24.37% drawing and 45.03% of losing against dealer’s HIT17, obviously this is a policy