feat: 重构项目结构并添加向量化PPO训练与评估脚本

- 将原始单环境训练代码重构为模块化结构，添加向量化环境支持以提高数据采集效率
- 实现完整的PPO训练流水线，包括共享CNN的Actor-Critic网络、向量化经验回放缓冲和GAE优势估计
- 添加训练脚本(train_vec.py)、评估脚本(evaluate.py)和SB3基线对比脚本(train_sb3_baseline.py)
- 提供详细的文档和开发日志，包含问题解决记录和实验分析
- 移除旧版项目文件，统一项目结构到CW1_id_name目录下

CW1_id_name/docs/eval_summary.json

@@ -0,0 +1,32 @@
+{
+  "checkpoint": "D:\\projects\\CW1_xxx\\models\\vec_main_v3\\iter_0700.pt",
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+  "mean": 830.1724279409364,
+  "std": 104.79337276485252,
+  "min": 436.8098159509071,
+  "max": 914.8999999999849,
+  "returns": [
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+    830.0291545189361,
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+}