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.py

@@ -2,6 +2,7 @@ from pipeline import Pipeline
 from algorithm.neat import *
 
 from problem.func_fit import XOR3d
+from utils import Act
 
 if __name__ == '__main__':
     pipeline = Pipeline(
@@ -10,13 +11,25 @@ if __name__ == '__main__':
                 genome=DefaultGenome(
                     num_inputs=3,
                     num_outputs=1,
-                    max_nodes=50,
-                    max_conns=100,
+                    max_nodes=100,
+                    max_conns=200,
+                    node_gene=DefaultNodeGene(
+                        activation_default=Act.tanh,
+                        activation_options=(Act.tanh,),
+                    ),
+                    output_transform=Act.sigmoid,  # the activation function for output node
                 ),
                 pop_size=10000,
                 species_size=10,
                 compatibility_threshold=3.5,
+                survival_threshold=0.01,  # magic
             ),
+            mutation=DefaultMutation(
+                node_add=0.05,
+                conn_add=0.2,
+                node_delete=0,
+                conn_delete=0,
+            )
         ),
         problem=XOR3d(),
         generation_limit=10000,