test

docs/10.md

@@ -21,9 +21,13 @@ $$
 我们将目标函数记为 $J(\theta)$，可以用蒙特卡洛方法估计 $J(\theta)$。我们用 $r(\tau)$ 来代表轨迹 $\tau$ 的衰减奖励总和。
 
 $$
-J(\theta) = \mathbb{E}_{\tau\sim \pi _{\theta}(\tau)}[\sum_t \gamma^t r (s_t,a_t)] = \int \pi_\theta(\tau)r(\tau)\text{d}\tau \approx \frac{1}{N}\sum_{i=1}^N \sum_{t=1}^T \gamma^t r(s_{i,t},a_{i,t})
+J(\theta) = \mathbb{E}_{\tau\sim \pi _{\theta}(\tau)}[\sum_t \gamma^t r (s_t,a_t)] = \int \pi_\theta(\tau)r(\tau)\text{d}\tau
 $$
 
+$$
+ \approx \frac{1}{N}\sum_{i=1}^N \sum_{t=1}^T \gamma^t r(s_{i,t},a_{i,t})
+ $$
+
 $$
 \theta^* = \mathop{\arg\max}_\theta J(\theta)
 $$
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