reinit

TankMan/ml/QT.py

@@ -0,0 +1,39 @@
+import numpy as np 
+import pandas as pd
+
+class QLearningTable:
+    def __init__(self,actions,learning_rate=0.05,reward_decay=0.9,e_greedy=0.1):
+       
+        self.actions=actions
+        self.lr=learning_rate
+        self.gamma=reward_decay
+        self.epsilon=e_greedy
+
+        self.q_table=pd.DataFrame(columns=self.actions,dtype=np.float64)                
+    
+    def choose_action(self,observation):
+        self.check_state_exist(observation)
+        
+        #action selection
+        if np.random.uniform()>self.epsilon:
+            state_action =self.q_table.loc[observation,:]                 
+            action =np.random.choice(state_action[state_action==np.max(state_action)].index)
+        else:
+            action = np.random.choice(self.actions)
+        
+        return action
+    
+    def learn(self,s,a,r,s_):
+        self.check_state_exist(s)
+        self.check_state_exist(s_)
+        q_predict=self.q_table.loc[s,a]
+        if s_!='Game_over' or s_!='Game_pass':
+            q_target =r+self.gamma*self.q_table.loc[s_,:].max()
+        else:
+            q_target=r
+        self.q_table.loc[s,a]+=self.lr*(q_target-q_predict)                
+    
+    def check_state_exist(self,state):
+        if state not in list(self.q_table.index):
+            new_row = pd.Series([0]*len(self.actions), index=self.q_table.columns, name=state)
+            self.q_table = pd.concat([self.q_table, pd.DataFrame(new_row).T])