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trpo_cartpole_recurrent.py
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trpo_cartpole_recurrent.py
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from rllab.algos.trpo import TRPO
from rllab.baselines.linear_feature_baseline import LinearFeatureBaseline
from rllab.envs.box2d.cartpole_env import CartpoleEnv
from rllab.envs.normalized_env import normalize
from rllab.policies.gaussian_gru_policy import GaussianGRUPolicy
from rllab.optimizers.conjugate_gradient_optimizer import ConjugateGradientOptimizer, FiniteDifferenceHvp
from rllab.misc.instrument import stub, run_experiment_lite
stub(globals())
env = normalize(CartpoleEnv())
policy = GaussianGRUPolicy(
env_spec=env.spec,
)
baseline = LinearFeatureBaseline(env_spec=env.spec)
algo = TRPO(
env=env,
policy=policy,
baseline=baseline,
batch_size=4000,
max_path_length=100,
n_itr=10,
discount=0.99,
step_size=0.01,
optimizer=ConjugateGradientOptimizer(hvp_approach=FiniteDifferenceHvp(base_eps=1e-5))
)
run_experiment_lite(
algo.train(),
n_parallel=1,
seed=1,
)