diff --git a/nucon/rl.py b/nucon/rl.py
index 0da1028..fa9158c 100644
--- a/nucon/rl.py
+++ b/nucon/rl.py
@@ -10,10 +10,13 @@ Objectives = {
     "coeff": lambda obj, coeff: lambda obs: obj(obs) * coeff,
 
     "max_power": lambda obs: obs["GENERATOR_0_KW"] + obs["GENERATOR_1_KW"] + obs["GENERATOR_2_KW"],
-    "target_temperature": lambda goal_temp: lambda obs: (obs["CORE_TEMP"] - goal_temp) ** 2,
     "episode_time": lambda obs: obs["EPISODE_TIME"],
 }
 
+Parameterized_Objectives = {
+    "target_temperature": lambda goal_temp: lambda obs: -((obs["CORE_TEMP"] - goal_temp) ** 2),
+}
+
 class NuconEnv(gym.Env):
     metadata = {'render_modes': ['human']}
 
@@ -140,4 +143,18 @@ class NuconEnv(gym.Env):
         return np.concatenate([v.flatten() for v in observation.values()])
 
     def _unflatten_observation(self, flat_observation):
-        return {k: v.reshape(1, -1) for k, v in self.observation_space.items()}
\ No newline at end of file
+        return {k: v.reshape(1, -1) for k, v in self.observation_space.items()}
+
+def register_nucon_envs():
+    gym.register(
+        id='Nucon-max_power-v0',
+        entry_point='nucon.rl:NuconEnv',
+        kwargs={'seconds_per_step': 5, 'objectives': ['max_power']}
+    )
+    gym.register(
+        id='Nucon-target_temperature_600-v0',
+        entry_point='nucon.rl:NuconEnv',
+        kwargs={'seconds_per_step': 5, 'objectives': [Parameterized_Objectives['target_temperature'](goal_temp=600)]}
+    )
+
+register_nucon_envs()
\ No newline at end of file