update q-learning

codes/Q-learning/params.py

@@ -0,0 +1,36 @@
+#!/usr/bin/env python
+# coding=utf-8
+'''
+Author: John
+Email: johnjim0816@gmail.com
+Date: 2020-11-24 19:45:58
+LastEditor: John
+LastEditTime: 2020-11-24 19:53:13
+Discription: 
+Environment: 
+'''
+import argparse
+import datetime
+import os
+
+SEQUENCE = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
+SAVED_MODEL_PATH = os.path.split(os.path.abspath(__file__))[0]+"/saved_model/"+SEQUENCE+'/'
+RESULT_PATH = os.path.split(os.path.abspath(__file__))[0]+"/result/"+SEQUENCE+'/'
+
+def get_args():
+    '''训练的模型参数
+    '''
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--train", default=1, type=int)  # 1 表示训练，0表示只进行eval
+    parser.add_argument("--gamma", default=0.9,
+                        type=float, help="reward 的衰减率") 
+    parser.add_argument("--epsilon_start", default=0.9,
+                        type=float,help="e-greedy策略中初始epsilon")  
+    parser.add_argument("--epsilon_end", default=0.1, type=float,help="e-greedy策略中的结束epsilon")
+    parser.add_argument("--epsilon_decay", default=200, type=float,help="e-greedy策略中epsilon的衰减率")
+    parser.add_argument("--policy_lr", default=0.1, type=float,help="学习率")
+    parser.add_argument("--max_episodes", default=500, type=int,help="训练的最大episode数目") 
+
+    config = parser.parse_args()
+
+    return config