diff --git a/pyproject.toml b/pyproject.toml
index 78d3d34..74956ba 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,11 +17,12 @@ classifiers = [
     "Topic :: Software Development :: Libraries :: Python Modules",
 ]
 dependencies = [
-    "shapiq>=1.2.3",
+    "shapiq==1.4.1",
     "numpy>=2.2.6",
     "scikit-learn>=1.7.1",
     "matplotlib>=3.10.5",
-    "networkx>=3.4.2"
+    "networkx>=3.4.2",
+    "ConfigSpace>=1.2.1",
 ]
 
 [project.urls]
@@ -50,8 +51,6 @@ docs = [
 ]
 
 dev = [
-    "shapiq>=1.2.0",
-    "ConfigSpace>=1.2.1",
     "numpy>=1.26.4",
     "tox-uv>=1.11.3",
     "deptry>=0.23.0",
diff --git a/src/hypershap/hypershap.py b/src/hypershap/hypershap.py
index 41fbff1..a3f74e0 100644
--- a/src/hypershap/hypershap.py
+++ b/src/hypershap/hypershap.py
@@ -12,6 +12,7 @@
 
 if TYPE_CHECKING:
     from ConfigSpace import Configuration
+    from shapiq import ValidApproximationIndices
 
     from hypershap.utils import ConfigSpaceSearcher
 
@@ -20,7 +21,8 @@
 import matplotlib.pyplot as plt
 import networkx as nx
 import numpy as np
-from shapiq import SHAPIQ, ExactComputer, InteractionValues, KernelSHAPIQ
+from shapiq import ExactComputer, InteractionValues
+from shapiq.explainer.configuration import setup_approximator_automatically
 
 from hypershap.games import (
     AblationGame,
@@ -66,13 +68,13 @@ class HyperSHAP:
         __init__(explanation_task: ExplanationTask):
             Initializes the HyperSHAP instance with an explanation task.
 
-        ablation(config_of_interest: Configuration, baseline_config: Configuration, index: str = "FSII", order: int = 2) -> InteractionValues:
+        ablation(config_of_interest: Configuration, baseline_config: Configuration, index: ValidApproximationIndices = "FSII", order: int = 2) -> InteractionValues:
             Computes and returns the interaction values for ablation analysis.
 
-        tunability(baseline_config: Configuration | None, index: str = "FSII", order: int = 2) -> InteractionValues:
+        tunability(baseline_config: Configuration | None, index: ValidApproximationIndices = "FSII", order: int = 2) -> InteractionValues:
             Computes and returns the interaction values for tunability analysis.
 
-        optimizer_bias(optimizer_of_interest: ConfigSpaceSearcher, optimizer_ensemble: list[ConfigSpaceSearcher], index: str = "FSII", order: int = 2) -> InteractionValues:
+        optimizer_bias(optimizer_of_interest: ConfigSpaceSearcher, optimizer_ensemble: list[ConfigSpaceSearcher], index: ValidApproximationIndices = "FSII", order: int = 2) -> InteractionValues:
             Computes and returns the interaction values for optimizer bias analysis.
 
         plot_si_graph(interaction_values: InteractionValues | None = None, save_path: str | None = None):
@@ -116,7 +118,13 @@ def __init__(
         )
         self.verbose = verbose
 
-    def __get_interaction_values(self, game: AbstractHPIGame, index: str = "FSII", order: int = 2) -> InteractionValues:
+    def __get_interaction_values(
+        self,
+        game: AbstractHPIGame,
+        index: ValidApproximationIndices = "FSII",
+        order: int = 2,
+        seed: int | None = 0,
+    ) -> InteractionValues:
         if game.n_players <= EXACT_MAX_HYPERPARAMETERS:
             # instantiate exact computer if number of hyperparameters is small enough
             ec = ExactComputer(n_players=game.get_num_hyperparameters(), game=game)  # pyright: ignore
@@ -124,11 +132,8 @@ def __get_interaction_values(self, game: AbstractHPIGame, index: str = "FSII", o
             # compute interaction values with the given index and order
             interaction_values = ec(index=index, order=order)
         else:
-            # instantiate kernel
-            if index == "FSII":
-                approx = SHAPIQ(n=game.n_players, max_order=2, index=index)
-            else:
-                approx = KernelSHAPIQ(n=game.n_players, max_order=2, index=index)
+            # instantiate approximator
+            approx = setup_approximator_automatically(index, order, game.n_players, seed)
 
             # approximate interaction values with the given index and order
             interaction_values = approx(budget=self.approximation_budget, game=game)
@@ -142,7 +147,7 @@ def ablation(
         self,
         config_of_interest: Configuration,
         baseline_config: Configuration,
-        index: str = "FSII",
+        index: ValidApproximationIndices = "FSII",
         order: int = 2,
     ) -> InteractionValues:
         """Compute and return the interaction values for ablation analysis.
@@ -150,7 +155,7 @@ def ablation(
         Args:
             config_of_interest (Configuration): The configuration of interest.
             baseline_config (Configuration): The baseline configuration.
-            index (str, optional): The index to use for computing interaction values. Defaults to "FSII".
+            index (ValidApproximationIndices, optional): The index to use for computing interaction values. Defaults to "FSII".
             order (int, optional): The order of the interaction values. Defaults to 2.
 
         Returns:
@@ -191,7 +196,7 @@ def ablation_multibaseline(
         config_of_interest: Configuration,
         baseline_configs: list[Configuration],
         aggregation: Aggregation = Aggregation.AVG,
-        index: str = "FSII",
+        index: ValidApproximationIndices = "FSII",
         order: int = 2,
     ) -> InteractionValues:
         """Compute and return the interaction values for multi-baseline ablation analysis.
@@ -200,7 +205,7 @@ def ablation_multibaseline(
             config_of_interest (Configuration): The configuration of interest.
             baseline_configs (list[Configuration]): The list of baseline configurations.
             aggregation (Aggregation): The aggregation method to use for computing interaction values.
-            index (str, optional): The index to use for computing interaction values. Defaults to "FSII".
+            index (ValidApproximationIndices, optional): The index to use for computing interaction values. Defaults to "FSII".
             order (int, optional): The order of the interaction values. Defaults to 2.
 
         Returns:
@@ -240,7 +245,7 @@ def ablation_multibaseline(
     def tunability(
         self,
         baseline_config: Configuration | None = None,
-        index: str = "FSII",
+        index: ValidApproximationIndices = "FSII",
         order: int = 2,
         n_samples: int = 10_000,
         seed: int | None = 0,
@@ -298,7 +303,7 @@ def tunability(
     def sensitivity(
         self,
         baseline_config: Configuration | None = None,
-        index: str = "FSII",
+        index: ValidApproximationIndices = "FSII",
         order: int = 2,
         n_samples: int = 10_000,
         seed: int | None = 0,
@@ -356,7 +361,7 @@ def sensitivity(
     def mistunability(
         self,
         baseline_config: Configuration | None = None,
-        index: str = "FSII",
+        index: ValidApproximationIndices = "FSII",
         order: int = 2,
         n_samples: int = 10_000,
         seed: int | None = 0,
@@ -365,7 +370,7 @@ def mistunability(
 
         Args:
             baseline_config (Configuration | None, optional): The baseline configuration. Defaults to None.
-            index (str, optional): The index to use for computing interaction values. Defaults to "FSII".
+            index (ValidApproximationIndices, optional): The index to use for computing interaction values. Defaults to "FSII".
             order (int, optional): The order of the interaction values. Defaults to 2.
             n_samples (int, optional): The number of samples to use for simulating HPO. Defaults to 10_000.
             seed (int, optiona): The random seed for simulating HPO. Defaults to 0.
@@ -414,7 +419,7 @@ def optimizer_bias(
         self,
         optimizer_of_interest: ConfigSpaceSearcher,
         optimizer_ensemble: list[ConfigSpaceSearcher],
-        index: str = "FSII",
+        index: ValidApproximationIndices = "FSII",
         order: int = 2,
     ) -> InteractionValues:
         """Compute and return the interaction values for optimizer bias analysis.
@@ -422,7 +427,7 @@ def optimizer_bias(
         Args:
             optimizer_of_interest (ConfigSpaceSearcher): The optimizer of interest.
             optimizer_ensemble (list[ConfigSpaceSearcher]): The ensemble of optimizers.
-            index (str, optional): The index to use for computing interaction values. Defaults to "FSII".
+            index (ValidApproximationIndices, optional): The index to use for computing interaction values. Defaults to "FSII".
             order (int, optional): The order of the interaction values. Defaults to 2.
 
         Returns:
diff --git a/src/hypershap/utils.py b/src/hypershap/utils.py
index 149092e..294ad6b 100644
--- a/src/hypershap/utils.py
+++ b/src/hypershap/utils.py
@@ -5,6 +5,7 @@
 
 from __future__ import annotations
 
+import logging
 from abc import ABC, abstractmethod
 from copy import deepcopy
 from enum import Enum
@@ -12,8 +13,15 @@
 
 if TYPE_CHECKING:
     from hypershap.task import BaselineExplanationTask
-
 import numpy as np
+from ConfigSpace.exceptions import (
+    ActiveHyperparameterNotSetError,
+    ForbiddenValueError,
+    IllegalVectorizedValueError,
+    InactiveHyperparameterSetError,
+)
+
+logger = logging.getLogger(__name__)
 
 
 class Aggregation(Enum):
@@ -106,6 +114,20 @@ def __init__(
         # cache coalition values to ensure monotonicity for min/max
         self.coalition_cache = {}
 
+    def _is_valid(self, config: np.ndarray) -> bool:
+        """Check whether a configuration is valid with respect to conditions of the configuration space."""
+        try:
+            self.explanation_task.config_space.check_configuration_vector_representation(config)
+        except (
+            ActiveHyperparameterNotSetError,
+            IllegalVectorizedValueError,
+            InactiveHyperparameterSetError,
+            ForbiddenValueError,
+        ):
+            return False
+        else:
+            return True
+
     def search(self, coalition: np.ndarray) -> float:
         """Search the configuration space based on the coalition.
 
@@ -125,6 +147,22 @@ def search(self, coalition: np.ndarray) -> float:
         column_index = np.where(blind_coalition)
         temp_random_sample[:, column_index] = self.explanation_task.baseline_config.get_array()[column_index]
 
-        # predict performance values with the help of the surrogate model
-        vals: np.ndarray = np.array(self.explanation_task.get_single_surrogate_model().evaluate(temp_random_sample))
+        # in case of conditions in the config space, it might happen that through blinding hyperparameter values
+        # configurations might become invalid and those should not be considered for calculating vals
+        if len(self.explanation_task.config_space.conditions) > 0:
+            # filter invalid configurations
+            validity = np.apply_along_axis(self._is_valid, axis=1, arr=temp_random_sample)
+            filtered_samples = temp_random_sample[validity]
+
+            if len(filtered_samples) < 0.05 * len(temp_random_sample):  # pragma: no cover
+                logger.warning(
+                    "WARNING: Due to blinding less than 5% of the samples in the random search remain valid. "
+                    "Consider increasing the sampling budget of the random search.",
+                )
+
+            # predict performance values with the help of the surrogate model for the filtered configurations
+            vals: np.ndarray = np.array(self.explanation_task.get_single_surrogate_model().evaluate(filtered_samples))
+        else:
+            vals: np.ndarray = np.array(self.explanation_task.get_single_surrogate_model().evaluate(temp_random_sample))
+
         return evaluate_aggregation(self.mode, vals)
diff --git a/tests/fixtures/simple_setup.py b/tests/fixtures/simple_setup.py
index 9bdd5b2..087f245 100644
--- a/tests/fixtures/simple_setup.py
+++ b/tests/fixtures/simple_setup.py
@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 import pytest
-from ConfigSpace import Configuration, ConfigurationSpace, UniformFloatHyperparameter
+from ConfigSpace import Configuration, ConfigurationSpace, LessThanCondition, UniformFloatHyperparameter
 
 from hypershap import ExplanationTask
 
@@ -41,7 +41,7 @@ def evaluate(self, x: Configuration) -> float:
         Returns: The value of the configuration.
 
         """
-        return self.value(x["a"], x["b"])
+        return self.value(x["a"], x.get("b", 0))
 
     def value(self, a: float, b: float) -> float:
         """Evaluate the value of a configuration.
@@ -71,3 +71,27 @@ def simple_base_et(
 ) -> ExplanationTask:
     """Return a base explanation task for the simple setup."""
     return ExplanationTask.from_function(simple_config_space, simple_blackbox_function.evaluate)
+
+
+@pytest.fixture(scope="session")
+def simple_cond_config_space() -> ConfigurationSpace:
+    """Return a simple config space with conditions for testing."""
+    config_space = ConfigurationSpace()
+    config_space.seed(42)
+
+    a = UniformFloatHyperparameter("a", 0, 1, 0)
+    b = UniformFloatHyperparameter("b", 0, 1, 0)
+    config_space.add(a)
+    config_space.add(b)
+
+    config_space.add(LessThanCondition(b, a, 0.3))
+    return config_space
+
+
+@pytest.fixture(scope="session")
+def simple_cond_base_et(
+    simple_cond_config_space: ConfigurationSpace,
+    simple_blackbox_function: SimpleBlackboxFunction,
+) -> ExplanationTask:
+    """Return a base explanation task for the simple setup with conditions."""
+    return ExplanationTask.from_function(simple_cond_config_space, simple_blackbox_function.evaluate)
diff --git a/tests/test_extended_settings.py b/tests/test_extended_settings.py
index 0acb07d..b01d1e0 100644
--- a/tests/test_extended_settings.py
+++ b/tests/test_extended_settings.py
@@ -72,3 +72,10 @@ def test_multi_data_sensitivity(multi_data_baseline_config: Configuration, hyper
     """Test the multi-data sesntivity task."""
     iv = hypershap_inst.sensitivity(baseline_config=multi_data_baseline_config)
     assert iv is not None, "Interaction values should not be none."
+
+
+def test_tunability_with_conditions(simple_cond_base_et: ExplanationTask) -> None:
+    """Test the tunability task with a configuration space that has conditions."""
+    hypershap = HyperSHAP(simple_cond_base_et)
+    iv = hypershap.tunability(simple_cond_base_et.config_space.get_default_configuration())
+    assert iv is not None, "Interaction values should not be none."
diff --git a/uv.lock b/uv.lock
index 00149ab..33e63f0 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1175,6 +1175,21 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/cf/58/8acf1b3e91c58313ce5cb67df61001fc9dcd21be4fadb76c1a2d540e09ed/fqdn-1.5.1-py3-none-any.whl", hash = "sha256:3a179af3761e4df6eb2e026ff9e1a3033d3587bf980a0b1b2e1e5d08d7358014", size = 9121, upload-time = "2021-03-11T07:16:28.351Z" },
 ]
 
+[[package]]
+name = "galois"
+version = "0.4.7"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numba" },
+    { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
+    { name = "numpy", version = "2.3.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/28/6c/e6343b658836a192d62bd1449f71444b6f0c8b0c1d75b37df50c45ffd4e3/galois-0.4.7.tar.gz", hash = "sha256:db71f979ebc99697fdd8c8fcb13529a37e6c0b4117595dc82e0377e2525fc2c3", size = 7338504, upload-time = "2025-11-07T23:56:48.877Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e1/6f/56d8b00c25ab5eaf1485e342d78b385025ceffe010b7a377e15329695bf1/galois-0.4.7-py3-none-any.whl", hash = "sha256:b6dc649f950e61ea2af07314c250c18be456605ac6b8823b701bae7cf7dff69a", size = 4171175, upload-time = "2025-11-07T23:56:46.977Z" },
+]
+
 [[package]]
 name = "ghp-import"
 version = "2.1.0"
@@ -1304,6 +1319,7 @@ name = "hypershap"
 version = "0.0.4"
 source = { editable = "." }
 dependencies = [
+    { name = "configspace" },
     { name = "matplotlib" },
     { name = "networkx", version = "3.4.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
     { name = "networkx", version = "3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
@@ -1318,7 +1334,6 @@ carps = [
     { name = "carps" },
 ]
 dev = [
-    { name = "configspace" },
     { name = "deptry" },
     { name = "mkdocs" },
     { name = "mkdocs-material" },
@@ -1332,7 +1347,6 @@ dev = [
     { name = "pytest-cov" },
     { name = "pytest-xdist" },
     { name = "ruff" },
-    { name = "shapiq" },
     { name = "tox-uv" },
 ]
 docs = [
@@ -1354,17 +1368,17 @@ test = [
 
 [package.metadata]
 requires-dist = [
+    { name = "configspace", specifier = ">=1.2.1" },
     { name = "matplotlib", specifier = ">=3.10.5" },
     { name = "networkx", specifier = ">=3.4.2" },
     { name = "numpy", specifier = ">=2.2.6" },
     { name = "scikit-learn", specifier = ">=1.7.1" },
-    { name = "shapiq", specifier = ">=1.2.3" },
+    { name = "shapiq", specifier = "==1.4.1" },
 ]
 
 [package.metadata.requires-dev]
 carps = [{ name = "carps", specifier = ">=1.0.4" }]
 dev = [
-    { name = "configspace", specifier = ">=1.2.1" },
     { name = "deptry", specifier = ">=0.23.0" },
     { name = "mkdocs", specifier = ">=1.4.2" },
     { name = "mkdocs-material", specifier = ">=8.5.10" },
@@ -1377,7 +1391,6 @@ dev = [
     { name = "pytest-cov", specifier = ">=6.0.0" },
     { name = "pytest-xdist", specifier = ">=3.6.1" },
     { name = "ruff", specifier = ">=0.11.5" },
-    { name = "shapiq", specifier = ">=1.2.0" },
     { name = "tox-uv", specifier = ">=1.11.3" },
 ]
 docs = [
@@ -1953,6 +1966,34 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/2d/00/d90b10b962b4277f5e64a78b6609968859ff86889f5b898c1a778c06ec00/lark-1.2.2-py3-none-any.whl", hash = "sha256:c2276486b02f0f1b90be155f2c8ba4a8e194d42775786db622faccd652d8e80c", size = 111036, upload-time = "2024-08-13T19:48:58.603Z" },
 ]
 
+[[package]]
+name = "llvmlite"
+version = "0.45.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/99/8d/5baf1cef7f9c084fb35a8afbde88074f0d6a727bc63ef764fe0e7543ba40/llvmlite-0.45.1.tar.gz", hash = "sha256:09430bb9d0bb58fc45a45a57c7eae912850bedc095cd0810a57de109c69e1c32", size = 185600, upload-time = "2025-10-01T17:59:52.046Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/cf/6d/585c84ddd9d2a539a3c3487792b3cf3f988e28ec4fa281bf8b0e055e1166/llvmlite-0.45.1-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:1b1af0c910af0978aa55fa4f60bbb3e9f39b41e97c2a6d94d199897be62ba07a", size = 43043523, upload-time = "2025-10-01T18:02:58.621Z" },
+    { url = "https://files.pythonhosted.org/packages/ae/34/992bd12d3ff245e0801bcf6013961daa8c19c9b9c2e61cb4b8bce94566f9/llvmlite-0.45.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:02a164db2d79088bbd6e0d9633b4fe4021d6379d7e4ac7cc85ed5f44b06a30c5", size = 37253122, upload-time = "2025-10-01T18:03:55.159Z" },
+    { url = "https://files.pythonhosted.org/packages/a6/7b/6d7585998a5991fa74dc925aae57913ba8c7c2efff909de9d34cc1cd3c27/llvmlite-0.45.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:f2d47f34e4029e6df3395de34cc1c66440a8d72712993a6e6168db228686711b", size = 56288210, upload-time = "2025-10-01T18:00:41.978Z" },
+    { url = "https://files.pythonhosted.org/packages/b5/e2/a4abea058633bfc82eb08fd69ce242c118fdb9b0abad1fdcbe0bc6aedab5/llvmlite-0.45.1-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f7319e5f9f90720578a7f56fbc805bdfb4bc071b507c7611f170d631c3c0f1e0", size = 55140958, upload-time = "2025-10-01T18:01:55.694Z" },
+    { url = "https://files.pythonhosted.org/packages/74/c0/233468e96ed287b953239c3b24b1d69df47c6ba9262bfdca98eda7e83a04/llvmlite-0.45.1-cp310-cp310-win_amd64.whl", hash = "sha256:4edb62e685867799e336723cb9787ec6598d51d0b1ed9af0f38e692aa757e898", size = 38132232, upload-time = "2025-10-01T18:04:41.538Z" },
+    { url = "https://files.pythonhosted.org/packages/04/ad/9bdc87b2eb34642c1cfe6bcb4f5db64c21f91f26b010f263e7467e7536a3/llvmlite-0.45.1-cp311-cp311-macosx_10_15_x86_64.whl", hash = "sha256:60f92868d5d3af30b4239b50e1717cb4e4e54f6ac1c361a27903b318d0f07f42", size = 43043526, upload-time = "2025-10-01T18:03:15.051Z" },
+    { url = "https://files.pythonhosted.org/packages/a5/ea/c25c6382f452a943b4082da5e8c1665ce29a62884e2ec80608533e8e82d5/llvmlite-0.45.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:98baab513e19beb210f1ef39066288784839a44cd504e24fff5d17f1b3cf0860", size = 37253118, upload-time = "2025-10-01T18:04:06.783Z" },
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