diff --git a/README.md b/README.md
index 43de3a13..061e7cf4 100644
--- a/README.md
+++ b/README.md
@@ -61,7 +61,7 @@ The architecture of the training pipeline is shown as follows:
 * For GPUs with 10G memory instead of 20G memory, you can allocate 0.25 gpu for each GPU maker (`@ray.remote(num_gpus=0.25)`) in `core/reanalyze_worker.py`.
 
 ### New environment registration
-If you wan to apply EfficientZero to a new environment like `mujoco`. Here are the steps for registration:
+If you want to apply EfficientZero to a new environment like `mujoco`, here are the steps for registration:
 1. Follow the directory `config/atari` and create dir for the env at `config/mujoco`.
 2. Implement your `MujocoConfig(BaseConfig)` class and implement the models as well as your environment wrapper.
 3. Register the case at `main.py`.