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change repo structure; modify readme

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wls2002
2024-03-26 21:58:27 +08:00
parent 6970e6a6d5
commit 47dbcbea80
69 changed files with 74 additions and 60 deletions
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32
examples/func_fit/xor.py
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@@ -1,32 +0,0 @@
from pipeline import Pipeline
from algorithm.neat import *
from problem.func_fit import XOR3d
if __name__ == '__main__':
pipeline = Pipeline(
algorithm=NEAT(
species=DefaultSpecies(
genome=DefaultGenome(
num_inputs=3,
num_outputs=1,
max_nodes=50,
max_conns=100,
),
pop_size=10000,
species_size=10,
compatibility_threshold=3.5,
),
),
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)

51
examples/func_fit/xor3d_hyperneat.py
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@@ -1,51 +0,0 @@
from pipeline import Pipeline
from algorithm.neat import *
from algorithm.hyperneat import *
from utils import Act
from problem.func_fit import XOR3d
if __name__ == '__main__':
pipeline = Pipeline(
algorithm=HyperNEAT(
substrate=FullSubstrate(
input_coors=[(-1, -1), (0.333, -1), (-0.333, -1), (1, -1)],
hidden_coors=[
(-1, -0.5), (0.333, -0.5), (-0.333, -0.5), (1, -0.5),
(-1, 0), (0.333, 0), (-0.333, 0), (1, 0),
(-1, 0.5), (0.333, 0.5), (-0.333, 0.5), (1, 0.5),
],
output_coors=[(0, 1), ],
),
neat=NEAT(
species=DefaultSpecies(
genome=DefaultGenome(
num_inputs=4, # [-1, -1, -1, 0]
num_outputs=1,
max_nodes=50,
max_conns=100,
node_gene=DefaultNodeGene(
activation_default=Act.tanh,
activation_options=(Act.tanh,),
),
),
pop_size=10000,
species_size=10,
compatibility_threshold=3.5,
),
),
activation=Act.sigmoid,
activate_time=10,
),
problem=XOR3d(),
generation_limit=300,
fitness_target=-1e-6
)
# initialize state
state = pipeline.setup()
# print(state)
# run until terminate
state, best = pipeline.auto_run(state)
# show result
pipeline.show(state, best)

41
examples/func_fit/xor_recurrent.py
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@@ -1,41 +0,0 @@
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
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=DefaultNodeGene(
activation_options=ACT_ALL,
# aggregation_options=AGG_ALL,
activation_replace_rate=0.2
),
),
pop_size=10000,
species_size=10,
compatibility_threshold=3.5,
),
),
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)