disable activation in the output node of network;

we recommend to use output_transform;
change hyperparameters (strong) in XOR example;

tensorneat/examples/func_fit/xor_recurrent.py

@@ -2,8 +2,7 @@ from pipeline import Pipeline
 from algorithm.neat import *
 
 from problem.func_fit import XOR3d
-from utils.activation import ACT_ALL
-from utils.aggregation import AGG_ALL
+from utils.activation import ACT_ALL, Act
 
 if __name__ == '__main__':
     pipeline = Pipeline(
@@ -18,14 +17,21 @@ if __name__ == '__main__':
                     activate_time=5,
                     node_gene=DefaultNodeGene(
                         activation_options=ACT_ALL,
-                        # aggregation_options=AGG_ALL,
                         activation_replace_rate=0.2
                     ),
+                    output_transform=Act.sigmoid
                 ),
                 pop_size=10000,
                 species_size=10,
                 compatibility_threshold=3.5,
+                survival_threshold=0.03,
             ),
+            mutation=DefaultMutation(
+                node_add=0.05,
+                conn_add=0.2,
+                node_delete=0,
+                conn_delete=0,
+            )
         ),
         problem=XOR3d(),
         generation_limit=10000,