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tensorneat-mend/tensorneat/examples/gymnax/reacher.py
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Python

import jax.numpy as jnp
from pipeline import Pipeline
from algorithm.neat import *
from problem.rl_env import GymNaxEnv
if __name__ == "__main__":
pipeline = Pipeline(
algorithm=NEAT(
species=DefaultSpecies(
genome=DefaultGenome(
num_inputs=8,
num_outputs=2,
max_nodes=50,
max_conns=100,
),
pop_size=10000,
species_size=10,
),
),
problem=GymNaxEnv(
env_name="Reacher-misc",
),
generation_limit=10000,
fitness_target=500,
)
# initialize state
state = pipeline.setup()
# print(state)
# run until terminate
state, best = pipeline.auto_run(state)