diff --git a/docs/chapter4/chapter4_questions&keywords.md b/docs/chapter4/chapter4_questions&keywords.md
index ec4f328..eb04dd4 100644
--- a/docs/chapter4/chapter4_questions&keywords.md
+++ b/docs/chapter4/chapter4_questions&keywords.md
@@ -83,10 +83,11 @@
   \theta^* = \theta + \alpha\nabla J({\theta})
   $$
   所以我们仅仅需要计算（更新）$\nabla J({\theta})$  ，也就是计算回报函数 $J({\theta})$ 关于 $\theta$ 的梯度，也就是策略梯度，计算方法如下：
-  $$
-  \nabla_{\theta}J(\theta) = \int {\nabla}_{\theta}p_{\theta}(\tau)r(\tau)d_{\tau}
-  =\int p_{\theta}{\nabla}_{\theta}logp_{\theta}(\tau)r(\tau)d_{\tau}=E_{\tau \sim p_{\theta}(\tau)}[{\nabla}_{\theta}logp_{\theta}(\tau)r(\tau)]
-  $$
+  $$\begin{aligned}
+  \nabla_{\theta}J(\theta) &= \int {\nabla}_{\theta}p_{\theta}(\tau)r(\tau)d_{\tau} \\
+  &= \int p_{\theta}{\nabla}_{\theta}logp_{\theta}(\tau)r(\tau)d_{\tau} \\
+  &= E_{\tau \sim p_{\theta}(\tau)}[{\nabla}_{\theta}logp_{\theta}(\tau)r(\tau)]
+  \end{aligned}$$
   接着我们继续讲上式展开，对于 $p_{\theta}(\tau)$ ，即 $p_{\theta}(\tau|{\theta})$ :
   $$
   p_{\theta}(\tau|{\theta}) = p(s_1)\prod_{t=1}^T \pi_{\theta}(a_t|s_t)p(s_{t+1}|s_t,a_t)