adjust parameter for xor problem

algorithms/neat/genome/distance.py

@@ -26,7 +26,7 @@ def distance(nodes1: Array, connections1: Array, nodes2: Array, connections2: Ar
 def node_distance(nodes1, nodes2, disjoint_coe=1., compatibility_coe=0.5):
     node_cnt1 = jnp.sum(~jnp.isnan(nodes1[:, 0]))
     node_cnt2 = jnp.sum(~jnp.isnan(nodes2[:, 0]))
-    max_cnt = jnp.maximum(node_cnt1, node_cnt2)
+    max_cnt = jnp.maximum(node_cnt1, node_cnt2) - 2
 
     nodes = jnp.concatenate((nodes1, nodes2), axis=0)
     keys = nodes[:, 0]
@@ -72,6 +72,7 @@ def connection_distance(cons1, cons2, disjoint_coe=1., compatibility_coe=0.5):
 
     return jnp.where(max_cnt == 0, 0, val / max_cnt)
 
+
 @vmap
 def batch_homologous_node_distance(b_n1, b_n2):
     return homologous_node_distance(b_n1, b_n2)

algorithms/neat/genome/origin_neat/__init__.py

@@ -16,7 +16,7 @@ def object2array(genome, N):
     nodes = np.full((N, 5), np.nan)
     connections = np.full((2, N, N), np.nan)
 
-    assert len(genome.nodes) + len(genome.input_keys) + 1 <= N  # remain one inf row for mutation adding extra node
+    assert len(genome.nodes) + len(genome.input_keys) <= N  # remain one inf row for mutation adding extra node
 
     idx = 0
     n2i = {}

algorithms/neat/genome/origin_neat/genome.py

@@ -18,8 +18,8 @@ class Genome:
         # Fitness results.
         self.fitness = None
 
-        self.input_keys = [-i - 1 for i in range(config.basic.num_inputs)]
-        self.output_keys = [i for i in range(config.basic.num_outputs)]
+        # self.input_keys = [-i - 1 for i in range(config.basic.num_inputs)]
+        # self.output_keys = [i for i in range(config.basic.num_outputs)]
 
         if init_val:
             self.initialize()