fancy_gym/alr_envs/__init__.py
2021-03-26 15:32:50 +01:00

132 lines
2.6 KiB
Python

from gym.envs.registration import register
from alr_envs.stochastic_search.functions.f_rosenbrock import Rosenbrock
register(
id='ALRReacher-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=200,
kwargs={
"steps_before_reward": 0,
"n_links": 5,
}
)
register(
id='ALRReacherSparse-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=200,
kwargs={
"steps_before_reward": 200,
"n_links": 5,
}
)
register(
id='ALRReacherSparseBalanced-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=200,
kwargs={
"steps_before_reward": 200,
"n_links": 5,
"balance": True,
}
)
register(
id='ALRReacherShort-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=50,
kwargs={
"steps_before_reward": 0,
"n_links": 5,
}
)
register(
id='ALRReacherShortSparse-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=50,
kwargs={
"steps_before_reward": 50,
"n_links": 5,
}
)
register(
id='ALRReacher7-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=200,
kwargs={
"steps_before_reward": 0,
"n_links": 7,
}
)
register(
id='ALRReacher7Sparse-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=200,
kwargs={
"steps_before_reward": 200,
"n_links": 7,
}
)
register(
id='ALRReacher7Short-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=50,
kwargs={
"steps_before_reward": 0,
"n_links": 7,
}
)
register(
id='ALRReacher7ShortSparse-v0',
entry_point='alr_envs.mujoco:ALRReacherEnv',
max_episode_steps=50,
kwargs={
"steps_before_reward": 50,
"n_links": 7,
}
)
register(
id='Balancing-v0',
entry_point='alr_envs.mujoco:BalancingEnv',
max_episode_steps=200,
kwargs={
"n_links": 5,
}
)
register(
id='SimpleReacher-v0',
entry_point='alr_envs.classic_control:SimpleReacherEnv',
max_episode_steps=200,
kwargs={
"n_links": 2,
}
)
register(
id='SimpleReacher5-v0',
entry_point='alr_envs.classic_control:SimpleReacherEnv',
max_episode_steps=200,
kwargs={
"n_links": 5,
}
)
for dim in [5, 10, 25, 50, 100]:
register(
id=f'Rosenbrock{dim}-v0',
entry_point='alr_envs.stochastic_search:StochasticSearchEnv',
max_episode_steps=1,
kwargs={
"cost_f": Rosenbrock,
}
)