rendering configuration

yycho0108 · May 3, 2018 · 4c83497 · 4c83497
1 parent 5d93c56
commit 4c83497
Showing 1 changed file with 4 additions and 5 deletions.
diff --git a/main_rnn.py b/main_rnn.py
@@ -18,6 +18,7 @@
 import sys
 import numpy as np
 import tensorflow as tf
+import time
 
 from memory import TraceMemory
 from drqn import DRQN
@@ -43,7 +44,7 @@
 ## Q-Learning Parameters
 GAMMA = .99 #Discount factor.
 N_EPOCH = np.inf #20000 #Total number of episodes to train network for.
-N_TEST = 1 #Total number of episodes to train network for.
+N_TEST = 200 #Total number of episodes to train network for.
 TAU = 1e-3#1e-3 #(1.0/100) * U_FREQ #Amount to update target network at each step.
 
 # Exploration Parameters
@@ -56,7 +57,7 @@
 N_PRE = int(1e5) #Number of steps, pre-train
 N_MEM = 10000 # ~5000 episodes
 
-GAME_STEPS = 5000
+GAME_STEPS = 999
 
 PARAMS = {
         'N_X' : N_X,
@@ -403,9 +404,6 @@ def test(self, n):
         sig = StopRequest()
         sig.start()
 
-        env.render()
-        x = raw_input('waiting ...')
-
         for i in range(n):
             if sig._stop:
                 break
@@ -429,6 +427,7 @@ def test(self, n):
                             })
                 s,r,d,_ = env.step(a[0])
                 net_reward += r
+                #time.sleep(0.01)
 
             print i, net_reward