85 lines
2.1 KiB
Python
85 lines
2.1 KiB
Python
import jax.numpy as jnp
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from config import *
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from pipeline import Pipeline
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from algorithm import NEAT
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from algorithm.neat.gene import NormalGene, NormalGeneConfig
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from problem.rl_env import GymNaxConfig, GymNaxEnv
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def example_conf1():
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return Config(
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basic=BasicConfig(
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seed=42,
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fitness_target=500,
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pop_size=10000
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),
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neat=NeatConfig(
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inputs=4,
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outputs=1,
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),
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gene=NormalGeneConfig(
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activation_default=Act.sigmoid,
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activation_options=(Act.sigmoid,),
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),
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problem=GymNaxConfig(
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env_name='CartPole-v1',
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output_transform=lambda out: jnp.where(out[0] > 0.5, 1, 0) # the action of cartpole is {0, 1}
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)
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)
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def example_conf2():
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return Config(
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basic=BasicConfig(
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seed=42,
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fitness_target=500,
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pop_size=10000
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),
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neat=NeatConfig(
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inputs=4,
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outputs=1,
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),
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gene=NormalGeneConfig(
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activation_default=Act.tanh,
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activation_options=(Act.tanh,),
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),
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problem=GymNaxConfig(
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env_name='CartPole-v1',
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output_transform=lambda out: jnp.where(out[0] > 0, 1, 0) # the action of cartpole is {0, 1}
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)
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)
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def example_conf3():
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return Config(
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basic=BasicConfig(
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seed=42,
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fitness_target=501,
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pop_size=10000
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),
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neat=NeatConfig(
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inputs=4,
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outputs=2,
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),
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gene=NormalGeneConfig(
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activation_default=Act.tanh,
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activation_options=(Act.tanh,),
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),
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problem=GymNaxConfig(
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env_name='CartPole-v1',
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output_transform=lambda out: jnp.argmax(out) # the action of cartpole is {0, 1}
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)
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)
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if __name__ == '__main__':
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# all config files above can solve cartpole
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conf = example_conf3()
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algorithm = NEAT(conf, NormalGene)
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pipeline = Pipeline(conf, algorithm, GymNaxEnv)
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state = pipeline.setup()
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pipeline.pre_compile(state)
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state, best = pipeline.auto_run(state)
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