minor

[shutbox.git] / src / qtable.py

diff --git a/src/qtable.py b/src/qtable.py
index 0804187c15694b0774f4f93daff23672c3f14467..fb650085955820d25d7fa0194763f9a384e79807 100755 (executable)
--- a/src/qtable.py
+++ b/src/qtable.py
@@ -6,7 +6,7 @@ import sys
 
 from game import Game
 
-learning_rate = 0.1
+learning_rate = 0.001
 discount_factor = 1.0
 
 states_dim = 36864 # 2^10 * 6^2
@@ -34,7 +34,6 @@ def select_option(opts, qs):
         opt_qid = find_option_qid(opt)
         opt_qid_pairs.append( [opt, opt_qid] )
         opt_qsum += qs[opt_qid]
-    #random.shuffle(opt_qid_pairs)
     ran_pt = random.uniform(0.0, opt_qsum)
     decision_pt = 0.0
     for opt_qid_pair in opt_qid_pairs:
@@ -57,14 +56,14 @@ for i in range(num_episodes):
             old_score = g.get_score()
             g.shut(opt)
             g.dice()
-            reward = (g.get_score() - old_score) / 11.0
+            reward = g.get_score() - old_score
             new_state_qid = find_state_qid(g.get_shutable(), g.get_diced())
             Q[state_qid, opt_qid] += \
                 learning_rate * (reward
                                  + discount_factor * np.max(Q[new_state_qid, :])
                                  - Q[state_qid, opt_qid])
             state_qid = new_state_qid
-    Q[state_qid, opt_qid] = 0
+    Q[state_qid, :] = 0.0
     running_score[0] *= 0.99999999
     running_score[0] += g.get_score()
     running_score[1] *= 0.99999999