diff --git a/alr_envs/classic_control/hole_reacher.py b/alr_envs/classic_control/hole_reacher.py
index 96c64f7..a5a153c 100644
--- a/alr_envs/classic_control/hole_reacher.py
+++ b/alr_envs/classic_control/hole_reacher.py
@@ -99,10 +99,10 @@ class HoleReacher(gym.Env):
             if self._steps == 199:
                 reward = - np.linalg.norm(self.end_effector - self.bottom_center_of_hole) ** 2
         else:
-            if self.collision_penalty != 0:
-                reward = -self.collision_penalty
-            else:
-                reward = - np.linalg.norm(self.end_effector - self.bottom_center_of_hole) ** 2
+            # if self.collision_penalty != 0:
+            #     reward = -self.collision_penalty
+            # else:
+            reward = - np.linalg.norm(self.end_effector - self.bottom_center_of_hole) ** 2 - self.collision_penalty
 
         reward -= 5e-8 * np.sum(acc ** 2)
 
diff --git a/alr_envs/classic_control/utils.py b/alr_envs/classic_control/utils.py
index 1aaafb1..89061cb 100644
--- a/alr_envs/classic_control/utils.py
+++ b/alr_envs/classic_control/utils.py
@@ -52,21 +52,22 @@ def make_holereacher_env(rank, seed=0):
         _env = HoleReacher(num_links=5,
                            allow_self_collision=False,
                            allow_wall_collision=False,
-                           hole_width=0.15,
+                           hole_width=0.25,
                            hole_depth=1,
-                           hole_x=1,
+                           hole_x=2,
                            collision_penalty=100)
 
         _env = DmpEnvWrapper(_env,
                              num_dof=5,
                              num_basis=5,
                              duration=2,
+                             bandwidth_factor=2,
                              dt=_env.dt,
                              learn_goal=True,
-                             alpha_phase=3.5,
+                             alpha_phase=2,
                              start_pos=_env.start_pos,
                              policy_type="velocity",
-                             weights_scale=100,
+                             weights_scale=50,
                              goal_scale=0.1
                              )
 
@@ -103,7 +104,7 @@ def make_holereacher_fix_goal_env(rank, seed=0):
                              dt=_env.dt,
                              learn_goal=False,
                              final_pos=np.array([2.02669572, -1.25966385, -1.51618198, -0.80946476,  0.02012344]),
-                             alpha_phase=3.5,
+                             alpha_phase=3,
                              start_pos=_env.start_pos,
                              policy_type="velocity",
                              weights_scale=50,
@@ -139,14 +140,15 @@ def make_holereacher_env_pmp(rank, seed=0):
         _env = DetPMPEnvWrapper(_env,
                                 num_dof=5,
                                 num_basis=5,
-                                width=0.025,
+                                width=0.02,
+                                off=0.,
                                 policy_type="velocity",
                                 start_pos=_env.start_pos,
                                 duration=2,
                                 post_traj_time=0,
                                 dt=_env.dt,
                                 weights_scale=0.2,
-                                zero_start=True,
+                                zero_start=False,
                                 zero_goal=False
                                 )
         _env.seed(seed + rank)
diff --git a/alr_envs/utils/dmp_env_wrapper.py b/alr_envs/utils/dmp_env_wrapper.py
index 5a2f27b..6835d80 100644
--- a/alr_envs/utils/dmp_env_wrapper.py
+++ b/alr_envs/utils/dmp_env_wrapper.py
@@ -14,8 +14,9 @@ class DmpEnvWrapper(gym.Wrapper):
                  start_pos=None,
                  final_pos=None,
                  duration=1,
-                 alpha_phase=2,
                  dt=0.01,
+                 alpha_phase=2,
+                 bandwidth_factor=3,
                  learn_goal=False,
                  post_traj_time=0.,
                  policy_type=None,
@@ -35,7 +36,10 @@ class DmpEnvWrapper(gym.Wrapper):
         self.post_traj_steps = int(post_traj_time / dt)
 
         phase_generator = ExpDecayPhaseGenerator(alpha_phase=alpha_phase, duration=duration)
-        basis_generator = DMPBasisGenerator(phase_generator, duration=duration, num_basis=self.num_basis)
+        basis_generator = DMPBasisGenerator(phase_generator,
+                                            duration=duration,
+                                            num_basis=self.num_basis,
+                                            basis_bandwidth_factor=bandwidth_factor)
 
         self.dmp = dmps.DMP(num_dof=num_dof,
                             basis_generator=basis_generator,
diff --git a/dmp_env_wrapper_example.py b/dmp_env_wrapper_example.py
index 2e526e5..bb886c6 100644
--- a/dmp_env_wrapper_example.py
+++ b/dmp_env_wrapper_example.py
@@ -8,21 +8,23 @@ if __name__ == "__main__":
 
     n_samples = 1
     n_cpus = 4
-    dim = 15
+    dim = 30
 
     # env = DmpAsyncVectorEnv([make_viapointreacher_env(i) for i in range(n_cpus)],
     #                         n_samples=n_samples)
 
-    test_env = make_holereacher_env_pmp(0)()
+    test_env = make_holereacher_env(0)()
 
     # params = 1 * np.random.randn(dim)
-    params = np.array([[ -0.13106822,  -0.66268577,  -1.37025136,  -1.34813613,
-         -0.34040336,  -1.41684643,   2.81882318,  -1.93383471,
-         -5.84213385,  -3.8623558 ,  -1.31946267,   3.19346678,
-         -9.6581148 ,  -8.27402906,  -0.42374776,  -2.06852054,
-          7.21224904,  -6.81061422,  -9.54973119,  -6.18636867,
-         -6.82998929,  13.00398992, -18.28106949,  -6.06678165,
-          2.79744735]])
+    params = np.array([ -1.09434772,   7.09294269,   0.98756352,   1.61950682,
+         2.66567135,   1.71267901,   8.20010847,   2.50496653,
+        -0.34886972,   2.07807773,   8.68615904,   3.66578556,
+         5.24572097,  -3.21506848,  -0.28593896,  17.03756855,
+        -5.88445032,   6.02197609,  -3.73457261,  -4.24772663,
+         8.69382861, -10.99939646,   5.31356886,   8.57420996,
+         1.05616879,  19.79831628, -23.53288774,  -3.32974082,
+        -5.86463784,  -9.68133089])
+
 
     # params = np.hstack([50 * np.random.randn(n_samples, 25), np.tile(np.array([np.pi/2, -np.pi/4, -np.pi/4, -np.pi/4, -np.pi/4]), [n_samples, 1])])