diff --git a/nevergrad/common/decorators.py b/nevergrad/common/decorators.py
index b263a26b0..d102e2f36 100644
--- a/nevergrad/common/decorators.py
+++ b/nevergrad/common/decorators.py
@@ -33,8 +33,8 @@ def register_name(
         self, name: str, obj: X, info: tp.Optional[tp.Dict[tp.Hashable, tp.Any]] = None
     ) -> None:
         """Register an object with a provided name"""
-        # if name in self:
-        #     raise RuntimeError(f'Encountered a name collision "{name}"')
+        if name in self:
+            raise RuntimeError(f'Encountered a name collision "{name}"')
         self[name] = obj
         if info is not None:
             assert isinstance(info, dict)
diff --git a/nevergrad/parametrization/core.py b/nevergrad/parametrization/core.py
index f2e52ae5c..edeeac2c5 100644
--- a/nevergrad/parametrization/core.py
+++ b/nevergrad/parametrization/core.py
@@ -42,7 +42,7 @@ class Parameter:
 
     value: ValueProperty[tp.Any] = ValueProperty()
 
-    def __init__(self, **parameters: tp.Any) -> None:
+    def __init__(self) -> None:
         # Main features
         self.uid = uuid.uuid4().hex
         self._treecall = utils.Treecall(self, Parameter)
@@ -50,7 +50,6 @@ def __init__(self, **parameters: tp.Any) -> None:
         self.heritage: tp.Dict[tp.Hashable, tp.Any] = {"lineage": self.uid}  # passed through to children
         self.loss: tp.Optional[float] = None  # associated loss
         self._losses: tp.Optional[np.ndarray] = None  # associated losses (multiobjective) as an array
-        self._parameters = None if not parameters else Dict(**parameters)  # internal/model parameters
         self._dimension: tp.Optional[int] = None
         # Additional convenient features
         self._random_state: tp.Optional[np.random.RandomState] = None  # lazy initialization
@@ -100,15 +99,6 @@ def kwargs(self) -> tp.Dict[str, tp.Any]:
         """
         return {}
 
-    @property
-    def parameters(self) -> "Dict":
-        """Internal/model parameters for this parameter"""
-        if self._parameters is None:  # delayed instantiation to avoid infinte loop
-            assert self.__class__ != Dict, "parameters of Parameters dict should never be called"
-            self._parameters = Dict()
-        assert self._parameters is not None
-        return self._parameters
-
     @property
     def dimension(self) -> int:
         """Dimension of the standardized space for this parameter
@@ -242,7 +232,7 @@ def get_value_hash(self) -> tp.Hashable:
         if isinstance(val, (str, bytes, float, int)):
             return val
         elif isinstance(val, np.ndarray):
-            return val.tobytes()
+            return val.tobytes()  # type: ignore
         else:
             raise utils.NotSupportedError(f"Value hash is not supported for object {self.name}")
 
@@ -262,8 +252,8 @@ def name(self) -> str:
         if self._name is not None:
             return self._name
         substr = ""
-        if self._parameters is not None and self.parameters:
-            substr = f"[{self.parameters._get_parameters_str()}]"
+        if hasattr(self, "parameters"):  # TODO temporary hack
+            substr = f"[{self.parameters._get_parameters_str()}]"  # type: ignore
             if substr == "[]":
                 substr = ""
         return f"{self._get_name()}" + substr
@@ -396,10 +386,10 @@ def _check_frozen(self) -> None:
 
     def _internal_spawn_child(self: P) -> P:
         # default implem just forwards params
-        inputs = {
-            k: v.spawn_child() if isinstance(v, Parameter) else v for k, v in self.parameters._content.items()
-        }
-        child = self.__class__(**inputs)
+        # inputs = {
+        #     k: v.spawn_child() if isinstance(v, Parameter) else v for k, v in self.parameters._content.items()
+        # }
+        child = self.__class__()  # **inputs)
         return child
 
     def copy(self: P) -> P:  # TODO test (see former instrumentation_copy test)
diff --git a/nevergrad/parametrization/data.py b/nevergrad/parametrization/data.py
index f67edd713..296990b6a 100644
--- a/nevergrad/parametrization/data.py
+++ b/nevergrad/parametrization/data.py
@@ -33,6 +33,10 @@ class Mutation(core.Parameter):
     # pylint: disable=unused-argument
     value: core.ValueProperty[tp.Callable[[tp.Sequence[D]], None]] = core.ValueProperty()
 
+    def __init__(self, **kwargs: tp.Any) -> None:
+        super().__init__()
+        self.parameters = core.Dict(**kwargs)
+
     def _get_value(self) -> tp.Callable[[tp.Sequence[D]], None]:
         return self.apply
 
@@ -80,7 +84,8 @@ def __init__(
         mutable_sigma: bool = False,
     ) -> None:
         sigma = Log(init=1.0, exponent=2.0, mutable_sigma=False) if mutable_sigma else 1.0
-        super().__init__(sigma=sigma, recombination="average", mutation="gaussian")
+        super().__init__()
+        self.parameters = core.Dict(sigma=sigma, recombination="average", mutation="gaussian")
         err_msg = 'Exactly one of "init" or "shape" must be provided'
         self.parameters._ignore_in_repr = dict(sigma="1.0", recombination="average", mutation="gaussian")
         if init is not None:
@@ -232,8 +237,7 @@ def set_bounds(
         return self
 
     def set_recombination(self: D, recombination: tp.Union[None, str, core.Parameter]) -> D:
-        assert self._parameters is not None
-        self._parameters._content["recombination"] = (
+        self.parameters._content["recombination"] = (
             recombination if isinstance(recombination, core.Parameter) else core.Constant(recombination)
         )
         return self
diff --git a/nevergrad/parametrization/helpers.py b/nevergrad/parametrization/helpers.py
index dd184b3b7..16df4680d 100644
--- a/nevergrad/parametrization/helpers.py
+++ b/nevergrad/parametrization/helpers.py
@@ -55,8 +55,8 @@ def flatten_parameter(
                         for x, y in content.items()
                     }
                 )
-    if order > 0 and parameter._parameters is not None:
-        subparams = flatten_parameter(parameter.parameters, with_containers=False, order=order - 1)
+    if order > 0 and hasattr(parameter, "parameters"):
+        subparams = flatten_parameter(parameter.parameters, with_containers=False, order=order - 1)  # type: ignore
         flat.update({"#" + str(x): y for x, y in subparams.items()})
     if not with_containers:
         flat = {