fix1.1.3 & 4-2 picture

docs/chapter1/Chapter1-Introduction-to-Agents.md

@@ -129,8 +129,8 @@ However, this powerful intuitive capability also comes with opacity. Sub-symboli
 
 For a long time, the two camps of symbolism and sub-symbolism developed like two parallel lines. To overcome the limitations of the above two paradigms, a "grand reconciliation" idea began to emerge, which is neuro-symbolic AI, also called neuro-symbolic hybrid. Its goal is to merge the advantages of both paradigms, creating a hybrid agent that can both learn from data like neural networks and perform logical reasoning like symbolic systems. It attempts to bridge the gap between perception and cognition, intuition and rationality. Nobel Prize-winning economist Daniel Kahneman's dual-system theory proposed in his book "Thinking, Fast and Slow" provides an excellent analogy for understanding neuro-symbolism<sup>[2]</sup>, as shown in Figure 1.4:
 
-- **System 1** is slow, methodical, logic-based deliberative thinking, just like the reasoning process of symbolic AI.
-- **System 2** is a fast, intuitive, parallel thinking mode, similar to the powerful pattern recognition capability of sub-symbolic AI.
+- **System 1** is a fast, intuitive, parallel thinking mode, similar to the powerful pattern recognition capability of sub-symbolic AI.
+- **System 2** is slow, methodical, logic-based deliberative thinking, just like the reasoning process of symbolic AI.
 
 <div align="center">
   <img src="https://raw.githubusercontent.com/datawhalechina/Hello-Agents/main/docs/images/1-figures/1757242319667-4.png" alt="Figure description" width="90%"/>

docs/chapter1/第一章 初识智能体.md

@@ -130,8 +130,8 @@
 
 长久以来，符号主义和亚符号主义这两大阵营如同两条平行线，各自发展。为克服上述两种范式的局限，一种“大和解”的思想开始兴起，这就是神经符号主义 AI，也称神经符号混合主义。它的目标，是融合两大范式的优点，创造出一个既能像神经网络一样从数据中学习，又能像符号系统一样进行逻辑推理的混合智能体。它试图弥合感知与认知、直觉与理性之间的鸿沟。诺贝尔经济学奖得主丹尼尔·卡尼曼（Daniel Kahneman）在其著作《思考，快与慢》（Thinking, Fast and Slow）中提出的双系统理论，为我们理解神经符号主义提供了一个绝佳的类比<sup>[2]</sup>，如图 1.4 所示：
 
-- <strong>系统 1</strong>是缓慢、有条理、基于逻辑的审慎思维，恰如符号主义 AI 的推理过程。
-- <strong>系统 2</strong>是快速、凭直觉、并行的思维模式，类似于亚符号主义 AI 强大的模式识别能力。
+- <strong>系统 1</strong>是快速、凭直觉、并行的思维模式，类似于亚符号主义 AI 强大的模式识别能力。
+- <strong>系统 2</strong>是缓慢、有条理、基于逻辑的审慎思维，恰如符号主义 AI 的推理过程。
 
 <div align="center">
   <img src="https://raw.githubusercontent.com/datawhalechina/Hello-Agents/main/docs/images/1-figures/1757242319667-4.png" alt="图片描述" width="90%"/>