diff --git a/README.md b/README.md
index c4bc7f2..2db6a00 100644
--- a/README.md
+++ b/README.md
@@ -102,15 +102,17 @@ The `NuconEnv` class in `nucon/rl.py` provides a Gym-compatible environment for
 - Observation space: Includes all readable parameters from the Nucon system.
 - Action space: Encompasses all writable parameters in the Nucon system.
 - Step function: Applies actions to the Nucon system and returns new observations.
-- Objective function: Allows for custom objective functions to be defined for training.
+- Objective function: Allows for predefined or custom objective functions to be defined for training.
 
 ### Usage
 
 Here's a basic example of how to use the RL environment:
 ```python
-from nucon.rl import NuconEnv
+from nucon.rl import NuconEnv, Parameterized_Objectives
 
 env = NuconEnv(objectives=['max_power'], seconds_per_step=5)
+# env2 = gym.make('Nucon-max_power-v0')
+# env3 = NuconEnv(objectives=[Parameterized_Objectives['target_temperature'](goal_temp=600)], seconds_per_step=5)
 
 obs, info = env.reset()
 for _ in range(1000):
@@ -122,6 +124,8 @@ for _ in range(1000):
 env.close()
 ```
 
+Objectives takes either strings of the name of predefined objectives, or lambda functions which take an observation and return a scalar reward. Final rewards are summed across all objectives. `info['objectives']` contains all objectives and their values.
+
 ## Testing
 
 NuCon includes a test suite to verify its functionality and compatibility with the Nucleares game.