diff --git a/SimCAD/configuration/__init__.py b/SimCAD/configuration/__init__.py
index d9b58e4..57951b6 100644
--- a/SimCAD/configuration/__init__.py
+++ b/SimCAD/configuration/__init__.py
@@ -73,9 +73,9 @@ class Processor:
         self.apply_identity_funcs = id.apply_identity_funcs
 
     def create_matrix_field(self, mechanisms, key):
-        if key == 'states':
+        if key == 'state_update_functions':
             identity = self.state_identity
-        elif key == 'behaviors':
+        elif key == 'policies':
             identity = self.behavior_identity
         df = pd.DataFrame(key_filter(mechanisms, key))
         col_list = self.apply_identity_funcs(identity, df, list(df.columns))
@@ -109,8 +109,19 @@ class Processor:
             return sdf_values, bdf_values
 
         if len(mechanisms) != 0:
-            bdf = self.create_matrix_field(mechanisms, 'behaviors')
-            sdf = self.create_matrix_field(mechanisms, 'states')
+            # for backwards compatibility we accept the old keys
+            # ('behaviors' and 'states') and rename them
+            for k, v in mechanisms.items():
+                try:
+                    v['policies'] = v.pop('behaviors')
+                except KeyError:
+                    pass
+                try:
+                    v['state_update_functions'] = v.pop('states')
+                except KeyError:
+                    pass
+            bdf = self.create_matrix_field(mechanisms, 'policies')
+            sdf = self.create_matrix_field(mechanisms, 'state_update_functions')
             sdf_values, bdf_values = no_update_handler(bdf, sdf)
             zipped_list = list(zip(sdf_values, bdf_values))
         else:
diff --git a/SimCAD/configuration/utils/__init__.py b/SimCAD/configuration/utils/__init__.py
index 53dad43..27da8c9 100644
--- a/SimCAD/configuration/utils/__init__.py
+++ b/SimCAD/configuration/utils/__init__.py
@@ -8,7 +8,7 @@ class TensorFieldReport:
     def __init__(self, config_proc):
         self.config_proc = config_proc
 
-    def create_tensor_field(self, mechanisms, exo_proc, keys=['behaviors', 'states']):
+    def create_tensor_field(self, mechanisms, exo_proc, keys=['policies', 'state_update_functions']):
         dfs = [self.config_proc.create_matrix_field(mechanisms, k) for k in keys]
         df = pd.concat(dfs, axis=1)
         for es, i in zip(exo_proc, range(len(exo_proc))):