Minor changes

qlearning.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python
-import sys,random,os
+import sys,random,os,statistics
 import numpy as np
 
 # Import snake game
@@ -119,7 +119,7 @@ class QTable:
                 generation+=self.save_every
                 with open(self.file+"_generation","w") as f:
                     f.write(str(generation))
-                print("Checkpointing generation "+str(generation))
+                print("----------------------------- Checkpointing generation "+str(generation))
             self.save_counter=0
 
     def get_action(self,state):
@@ -140,8 +140,9 @@ class QTable:
 
 
 # Perform learning
-width,height=10,10
+width,height=40,30 # My advice is start with a small grid 5x5 to have many interaction and avoid early toy effect
 perf=0
+perf_list=list()
 last_state=None
 last_action=None
 game=Snake(length=1,fps=500,startat=(random.randint(0,width-1),random.randint(0,height-1)),grid_width=width,grid_height=height)
@@ -172,8 +173,8 @@ while True:
         if stuck>=(game.grid_width*game.grid_height)/stuck_tolerance:
             stuck=0
             stuck_count+=1
-            action=qtable.get_random_action()
-            print("Stuck! Try a random action...")
+            game.new_apple()
+            print("Stuck! Try with a new apple...")
         if stuck_count>2:
             print("Can't get out of stuck. Abort!")
             stuck_count=0
@@ -187,5 +188,6 @@ while True:
 
     # Measurements
     score=game.last_score
+    perf_list.append(score)
     perf=max(perf,score)
-    print("Game ended with "+str(score)+"  best so far is "+str(perf))
+    print("Game ended with "+str(score)+"  best so far is "+str(perf)+ " median is "+str(statistics.median(perf_list)))

qtable.txt_generation

@@ -1 +1 @@
-15000
+400000