diff --git a/scripts/algorithms/common/abstract/agent.py b/scripts/algorithms/common/abstract/agent.py
index 67f205b..9c802c6 100644
--- a/scripts/algorithms/common/abstract/agent.py
+++ b/scripts/algorithms/common/abstract/agent.py
@@ -14,7 +14,7 @@ import numpy as np
 import torch
 
 
-class AbstractAgent:
+class AbstractAgent(object):
     """Abstract Agent used for all agents.
 
     Attributes:
diff --git a/scripts/algorithms/common/buffer/replay_buffer.py b/scripts/algorithms/common/buffer/replay_buffer.py
index b870e16..1ac16d0 100644
--- a/scripts/algorithms/common/buffer/replay_buffer.py
+++ b/scripts/algorithms/common/buffer/replay_buffer.py
@@ -11,7 +11,7 @@ from algorithms.common.helper_functions import get_n_step_info
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 
-class ReplayBuffer:
+class ReplayBuffer(object):
     """Fixed-size buffer to store experience tuples.
 
     Taken from Udacity deep-reinforcement-learning github repository:
@@ -79,7 +79,7 @@ class ReplayBuffer:
         return len(self.buffer)
 
 
-class NStepTransitionBuffer:
+class NStepTransitionBuffer(object):
     """Fixed-size buffer to store experience tuples.
 
     Attributes:
diff --git a/scripts/algorithms/common/buffer/segment_tree.py b/scripts/algorithms/common/buffer/segment_tree.py
index 153003d..30fd410 100644
--- a/scripts/algorithms/common/buffer/segment_tree.py
+++ b/scripts/algorithms/common/buffer/segment_tree.py
@@ -4,7 +4,7 @@
 import operator
 
 
-class SegmentTree:
+class SegmentTree(object):
     """ Create SegmentTree.
 
     Taken from OpenAI baselines github repository:
diff --git a/scripts/algorithms/common/noise.py b/scripts/algorithms/common/noise.py
index 6b2f941..bcf5277 100644
--- a/scripts/algorithms/common/noise.py
+++ b/scripts/algorithms/common/noise.py
@@ -7,7 +7,7 @@ import random
 import numpy as np
 
 
-class GaussianNoise:
+class GaussianNoise(object):
     """Gaussian Noise.
 
     Taken from https://github.com/vitchyr/rlkit
@@ -28,7 +28,7 @@ class GaussianNoise:
         return np.random.normal(0, sigma, size=self.action_dim)
 
 
-class OUNoise:
+class OUNoise(object):
     """Ornstein-Uhlenbeck process.
 
     Taken from Udacity deep-reinforcement-learning github repository:
diff --git a/scripts/data/lunarlander_continuous_demo.pkl b/scripts/data/lunarlander_continuous_demo.pkl
index fe52886..5bc30fb 100644
Binary files a/scripts/data/lunarlander_continuous_demo.pkl and b/scripts/data/lunarlander_continuous_demo.pkl differ
diff --git a/scripts/data/reacher_demo.pkl b/scripts/data/reacher_demo.pkl
index 0cd3e88..6500289 100644
Binary files a/scripts/data/reacher_demo.pkl and b/scripts/data/reacher_demo.pkl differ