diff --git a/chainerrl/agents/dqn.py b/chainerrl/agents/dqn.py
index a59e5cad2..fd8e454c9 100644
--- a/chainerrl/agents/dqn.py
+++ b/chainerrl/agents/dqn.py
@@ -352,19 +352,39 @@ def _compute_loss(self, exp_batch, gamma, errors_out=None):
             return compute_value_loss(y, t, clip_delta=self.clip_delta,
                                       batch_accumulator=self.batch_accumulator)
 
-    def act(self, obs):
+    def act_with_exploration(self, obs):
+
         with chainer.using_config('train', False):
             with chainer.no_backprop_mode():
                 action_value = self.model(
                     self.batch_states([obs], self.xp, self.phi))
                 q = float(action_value.max.data)
-                action = cuda.to_cpu(action_value.greedy_actions.data)[0]
-
+                greedy_action = cuda.to_cpu(action_value.greedy_actions.data)[0]
+                
+        action = self.explorer.select_action(self.t,
+                    lambda: greedy_action,
+                    action_value=action_value)
+        self.t += 1
         # Update stats
         self.average_q *= self.average_q_decay
         self.average_q += (1 - self.average_q_decay) * q
 
         self.logger.debug('t:%s q:%s action_value:%s', self.t, q, action_value)
+        return action
+        
+    def act(self, obs):
+        with chainer.using_config('train', False):
+            with chainer.no_backprop_mode():
+                action_value = self.model(
+                    self.batch_states([obs], self.xp, self.phi))
+                q = float(action_value.max.data)
+                action = cuda.to_cpu(action_value.greedy_actions.data)[0]
+
+        # Update stats
+        self.average_q *= self.average_q_decay
+        self.average_q += (1 - self.average_q_decay) * q
+
+        self.logger.debug('t:%s q:%s action_value:%s', self.t, q, action_value)
         return action
 
     def act_and_train(self, obs, reward):