世界是空格自由（0）或障碍物（1）。每转动机器人可以在8个方向移动，或者留在地方。奖励功能，给人一种自由空间，目标定位，高回报。所有其他空格自由具有小的损失，和障碍具有大的负的奖励。值迭代是用来学习的最佳“政策”，即指定一个控制输入到每一个可能的位置的功能。- The world is freespaces (0) or obstacles (1). Each turn the robot can move in 8 directions, or stay in place. A reward function gives one freespace, the goal location, a high reward. All other freespaces have a small penalty, and obstacles have a large negative reward. Value iteration is used to learn an optimal　policy , a function that assigns a control input to every possible location.