diff --git a/__pycache__/nim.cpython-313.pyc b/__pycache__/nim.cpython-313.pyc
index 181141d..af19071 100644
Binary files a/__pycache__/nim.cpython-313.pyc and b/__pycache__/nim.cpython-313.pyc differ
diff --git a/nim.py b/nim.py
index bce6111..ad1a42c 100644
--- a/nim.py
+++ b/nim.py
@@ -95,15 +95,17 @@ class NimAI():
         float: The highest Q-value among available actions. 
                Returns 0 if no actions are available.
     """
+        state = tuple(state)
         # actions = []
-        # for q in self.q.key:
-        #     if q[0] == state:
+        # for q in self.q:
+        #     print(q)
+        #     if q[0] == tuple(state):
         #         actions.append(q[1])
-        actions = tuple([key[1] for key in self.q.keys() if key[0] == state])
-        try:
-            return max([q for q in self.q[tuple(state), actions]])
-        except:
-            return 0
+        actions = [key[1] for key in self.q if key[0] == state]
+        # print(actions)
+        # print(self.q[state, action] for action in actions)
+        # print(max(self.q[state, action] for action in actions))
+        return 0 if actions == [] else max(self.q[state, action] for action in actions)
 
     def choose_action(self, state, epsilon=True):
         """
diff --git a/test.py b/test.py
index dfa2c8b..3a974b3 100644
--- a/test.py
+++ b/test.py
@@ -19,6 +19,8 @@ def test_update_q_value(ai):
 
 def test_best_future_reward(ai):
     print("\n--- Testing best_future_reward ---")
+    print(ai.best_future_reward([1,1,1,0]))
+    print(ai.best_future_reward([1,1,1,1]))
 
 
 def test_choose_action(ai):