diff --git a/README.md b/README.md
index 2c8acb4..e193711 100644
--- a/README.md
+++ b/README.md
@@ -28,7 +28,7 @@ After importing `pystk2_gymnasium`, the following environments are available:
     - `difficulty` is the difficulty of the other bots (0 to 2, default to 2)
 - `supertuxkart-simple-v0` is a simplified environment with fixed number of observations for paths (controlled by `state_paths`, default 5), items (`state_items`, default 5), karts (`state_karts`, default 5)
 - `supertuxkart-flattened-v0` has observation and action spaces simplified at the maximum (only `discrete` and `continuous` keys)
-- `supertuxkart-flattened-multidiscrete-v0` is like the previous one, but with fully multi-discrete actions
+- `supertuxkart-flattened-multidiscrete-v0` is like the previous one, but with fully multi-discrete actions. `acceleration_steps` and `steer_steps` (default to 5) control the number of discrete values for acceleration and steering respectively.
 - `supertuxkart-flattened-discrete-v0` is like the previous one, but with fully discretized actions
 
 The reward is the distance traveled.
diff --git a/src/pystk2_gymnasium/envs.py b/src/pystk2_gymnasium/envs.py
index fef6b9c..58e2ee6 100644
--- a/src/pystk2_gymnasium/envs.py
+++ b/src/pystk2_gymnasium/envs.py
@@ -482,7 +482,7 @@ def continuous(self, value: int):
 
 class DiscreteActionSTKRaceEnv(SimpleSTKRaceEnv):
     # Wraps the actions
-    def __init__(self, acceleration_steps=10, steer_steps=10, **kwargs):
+    def __init__(self, acceleration_steps=5, steer_steps=5, **kwargs):
         super().__init__(**kwargs)
 
         self.d_acceleration = Discretizer(