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tensorneat-mend/tensorneat/examples/func_fit/xor_recurrent.py
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Python

from pipeline import Pipeline
from algorithm.neat import *
from algorithm.neat.gene.node.default_without_response import NodeGeneWithoutResponse
from problem.func_fit import XOR3d
from utils.activation import ACT_ALL, Act
if __name__ == "__main__":
pipeline = Pipeline(
seed=0,
algorithm=NEAT(
species=DefaultSpecies(
genome=RecurrentGenome(
num_inputs=3,
num_outputs=1,
max_nodes=50,
max_conns=100,
activate_time=5,
node_gene=NodeGeneWithoutResponse(
activation_options=ACT_ALL, activation_replace_rate=0.2
),
output_transform=Act.sigmoid,
mutation=DefaultMutation(
node_add=0.05,
conn_add=0.2,
node_delete=0,
conn_delete=0,
),
),
pop_size=10000,
species_size=10,
compatibility_threshold=3.5,
survival_threshold=0.03,
),
),
problem=XOR3d(),
generation_limit=10000,
fitness_target=-1e-8,
)
# initialize state
state = pipeline.setup()
# print(state)
# run until terminate
state, best = pipeline.auto_run(state)
# show result
pipeline.show(state, best)