complete HyperNEAT!

config/default_config.ini

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+[basic]
+random_seed = 0
+generation_limit = 1000
+
+[problem]
+fitness_threshold = 3.9999
+num_inputs = 2
+num_outputs = 1
+
+[neat]
+network_type = "feedforward"
+activate_times = 5
+maximum_nodes = 50
+maximum_conns = 50
+maximum_species = 10
+
+[hyperneat]
+below_threshold = 0.2
+max_weight = 3
+h_activation = "sigmoid"
+h_aggregation = "sum"
+h_activate_times = 5
+
+[substrate]
+input_coors = [[-1, 1], [0, 1], [1, 1]]
+hidden_coors = [[-1, 0], [0, 0], [1, 0]]
+output_coors = [[0, -1]]
+
+[population]
+pop_size = 10
+
+[genome]
+compatibility_disjoint = 1.0
+compatibility_weight = 0.5
+conn_add_prob = 0.4
+conn_delete_prob = 0
+node_add_prob = 0.2
+node_delete_prob = 0
+
+[species]
+compatibility_threshold = 3.0
+species_elitism = 2
+max_stagnation = 15
+genome_elitism = 2
+survival_threshold = 0.2
+min_species_size = 1
+spawn_number_change_rate = 0.5
+
+[gene]
+# bias
+bias_init_mean = 0.0
+bias_init_std = 1.0
+bias_mutate_power = 0.5
+bias_mutate_rate = 0.7
+bias_replace_rate = 0.1
+
+# response
+response_init_mean = 1.0
+response_init_std = 0.0
+response_mutate_power = 0.0
+response_mutate_rate = 0.0
+response_replace_rate = 0.0
+
+# activation
+activation_default = "sigmoid"
+activation_option_names = ["tanh"]
+activation_replace_rate = 0.0
+
+# aggregation
+aggregation_default = "sum"
+aggregation_option_names = ["sum"]
+aggregation_replace_rate = 0.0
+
+# weight
+weight_init_mean = 0.0
+weight_init_std = 1.0
+weight_mutate_power = 0.5
+weight_mutate_rate = 0.8
+weight_replace_rate = 0.1
+
+[visualize]
+renumber_nodes = True