diff --git a/navix/_version.py b/navix/_version.py
index a4beb31..397649b 100644
--- a/navix/_version.py
+++ b/navix/_version.py
@@ -18,5 +18,5 @@
 # under the License.
 
 
-__version__ = "0.3.8"
+__version__ = "0.3.9"
 __version_info__ = tuple(int(i) for i in __version__.split(".") if i.isdigit())
diff --git a/navix/environments/environment.py b/navix/environments/environment.py
index 225965d..eca7f54 100644
--- a/navix/environments/environment.py
+++ b/navix/environments/environment.py
@@ -20,7 +20,6 @@
 
 from __future__ import annotations
 
-import sys
 import abc
 from enum import IntEnum
 from typing import Any, Callable, Dict
@@ -84,10 +83,10 @@ def observation_space(self) -> Space:
         if self.observation_fn == observations.none:
             return Continuous(shape=())
         elif self.observation_fn == observations.categorical:
-            return Discrete(sys.maxsize, shape=(self.height, self.width))
+            return Discrete(shape=(self.height, self.width))
         elif self.observation_fn == observations.categorical_first_person:
             radius = observations.RADIUS
-            return Discrete(sys.maxsize, shape=(radius + 1, radius * 2 + 1))
+            return Discrete(shape=(radius + 1, radius * 2 + 1))
         elif self.observation_fn == observations.rgb:
             return Discrete(
                 256,
diff --git a/navix/spaces.py b/navix/spaces.py
index 66e0011..748908d 100644
--- a/navix/spaces.py
+++ b/navix/spaces.py
@@ -14,7 +14,6 @@
 
 
 from __future__ import annotations
-from typing import Callable
 
 import jax
 import jax.numpy as jnp
@@ -25,13 +24,15 @@
 from jax.core import ShapedArray, Shape
 
 
-POS_INF = jnp.asarray(1e16)
-NEG_INF = jnp.asarray(-1e16)
+MIN_INT = jax.numpy.iinfo(jnp.int16).min
+MAX_INT = jax.numpy.iinfo(jnp.int16).max
+MIN_INT_ARR = jnp.asarray(MIN_INT)
+MAX_INT_ARR = jnp.asarray(MAX_INT)
 
 
 class Space(ShapedArray):
-    minimum: Array = NEG_INF
-    maximum: Array = POS_INF
+    minimum: Array = MIN_INT_ARR
+    maximum: Array = MAX_INT_ARR
 
     def __repr__(self):
         return "{}, min={}, max={})".format(
@@ -43,19 +44,21 @@ def sample(self, key: KeyArray) -> Array:
 
 
 class Discrete(Space):
-    def __init__(self, n_elements: int, shape: Shape = (), dtype=jnp.int32):
+    def __init__(self, n_elements: int = MAX_INT, shape: Shape = (), dtype=jnp.int32):
         super().__init__(shape, dtype)
         self.minimum = jnp.asarray(0)
         self.maximum = jnp.asarray(n_elements - 1)
 
     def sample(self, key: KeyArray) -> Array:
-        return jax.random.randint(
-            key, self.shape, self.minimum, self.maximum, self.dtype
+        item = jax.random.randint(
+            key, self.shape, self.minimum, self.maximum
         )
+        # randint cannot draw jnp.uint, so we cast it later
+        return jnp.asarray(item, dtype=self.dtype)
 
 
 class Continuous(Space):
-    def __init__(self, shape: Shape = (), minimum=NEG_INF, maximum=POS_INF):
+    def __init__(self, shape: Shape = (), minimum=MIN_INT_ARR, maximum=MAX_INT_ARR):
         super().__init__(shape, jnp.float32)
         self.minimum = minimum
         self.maximum = maximum
diff --git a/tests/test_spaces.py b/tests/test_spaces.py
new file mode 100644
index 0000000..3901259
--- /dev/null
+++ b/tests/test_spaces.py
@@ -0,0 +1,34 @@
+import jax
+import jax.numpy as jnp
+from navix.spaces import Space, Continuous, Discrete, MAX_INT, MIN_INT
+
+
+def test_discrete():
+    key = jax.random.PRNGKey(42)
+    elements = (5, 0, MAX_INT, MIN_INT)
+    shapes = ((), (0,), (0, 0), (1, 2), (5, 5))
+    dtypes = (jnp.int8, jnp.int16, jnp.int32)
+    for element in elements:
+        for shape in shapes:
+            for dtype in dtypes:
+                space = Discrete(element, shape, dtype)
+                sample = space.sample(key)
+                print(sample)
+                assert jnp.all(jnp.logical_not(jnp.isnan(sample)))
+
+
+def test_continuous():
+    key = jax.random.PRNGKey(42)
+    shapes = ((), (0,), (0, 0), (1, 2), (5, 5))
+    min_max = [(0.0, 1.0), (0.0, 1), (0, 1), (1.0, -1.0), (MIN_INT, MAX_INT),]
+    for shape in shapes:
+        for minimum, maximum in min_max:
+            space = Continuous(shape=shape, minimum=jnp.asarray(minimum), maximum=jnp.asarray(maximum))
+            sample = space.sample(key)
+            print(sample)
+            assert jnp.all(jnp.logical_not(jnp.isnan(sample)))
+
+
+if __name__ == '__main__':
+    test_discrete()
+    test_continuous()
\ No newline at end of file