123 lines
2.4 KiB
Python
123 lines
2.4 KiB
Python
from gym.envs.registration import register
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from alr_envs.stochastic_search.functions.f_rosenbrock import Rosenbrock
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register(
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id='ALRReacher-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=200,
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kwargs={
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"steps_before_reward": 0,
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"n_links": 5,
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}
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)
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register(
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id='ALRReacherSparse-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=200,
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kwargs={
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"steps_before_reward": 200,
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"n_links": 5,
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}
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)
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register(
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id='ALRReacherSparseBalanced-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=200,
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kwargs={
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"steps_before_reward": 200,
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"n_links": 5,
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"balance": True,
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}
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)
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register(
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id='ALRReacherShort-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=50,
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kwargs={
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"steps_before_reward": 0,
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"n_links": 5,
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}
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)
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register(
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id='ALRReacherShortSparse-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=50,
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kwargs={
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"steps_before_reward": 50,
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"n_links": 5,
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}
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)
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register(
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id='ALRReacher7-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=200,
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kwargs={
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"steps_before_reward": 0,
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"n_links": 7,
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}
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)
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# register(
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# id='ALRReacherSparse-v0',
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# entry_point='alr_envs.mujoco:ALRReacherEnv',
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# max_episode_steps=200,
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# kwargs={
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# "steps_before_reward": 200,
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# "n_links": 7,
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# }
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# )
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register(
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id='ALRReacher7Short-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=50,
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kwargs={
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"steps_before_reward": 0,
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"n_links": 7,
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}
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)
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register(
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id='ALRReacher7ShortSparse-v0',
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entry_point='alr_envs.mujoco:ALRReacherEnv',
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max_episode_steps=50,
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kwargs={
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"steps_before_reward": 50,
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"n_links": 7,
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}
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)
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register(
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id='SimpleReacher-v0',
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entry_point='alr_envs.classic_control:SimpleReacherEnv',
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max_episode_steps=200,
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kwargs={
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"n_links": 2,
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}
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)
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register(
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id='SimpleReacher5-v0',
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entry_point='alr_envs.classic_control:SimpleReacherEnv',
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max_episode_steps=200,
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kwargs={
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"n_links": 5,
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}
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)
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for dim in [5, 10, 25, 50, 100]:
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register(
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id=f'Rosenbrock{dim}-v0',
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entry_point='alr_envs.stochastic_search:StochasticSearchEnv',
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max_episode_steps=1,
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kwargs={
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"cost_f": Rosenbrock,
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}
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)
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