def set_env():
register(
id='SnakeEnv-v0',
entry_point='gym.envs.gym_snake:SingleSnake',
)
add_group(id='gym_snake', name='gym_snake', description='snake')
add_task(id='SnakeEnv-v0',
group='gym_snake',
summary="Multi snakes environment")
from gym.envs.registration import register
from gym.scoreboard.registration import add_task, add_group
from .package_info import USERNAME
# Environment registration
for d in [4, 8, 16, 32, 64]:
register(
id='{}/gridworld-{}x{}'.format(USERNAME, d, d),
entry_point='{}_gym_gridworld:GridWorldEnv'.format(USERNAME),
max_episode_steps=1000,
reward_threshold=9000.0,
kwargs={'dimension': d},
)
# Scoreboard registration
# ==========================
add_group(id='gridworld',
name='GridWorld',
description='Sutton & Barto classic Gridworld environment.')
for d in [4, 8, 16, 32, 64]:
add_task(id='{}/GridWorld-{}x{}'.format(USERNAME, d, d),
group='gridworld',
summary='Sutton and Barto Grid world, {}x{}.'.format(d),
description="""
""")
from gym.scoreboard.registration import registry, add_task, add_group
# Discover API key from the environment. (You should never have to
# change api_base / web_base.)
api_key = os.environ.get('OPENAI_GYM_API_KEY')
api_base = os.environ.get('OPENAI_GYM_API_BASE', 'https://gym-api.openai.com')
web_base = os.environ.get('OPENAI_GYM_WEB_BASE', 'https://gym.openai.com')
# The following controls how various tasks appear on the
# scoreboard. These registrations can differ from what's registered in
# this repository.
# groups
add_group(id='classic_control',
name='Classic control',
description='Classic control problems from the RL literature.')
add_group(
id='algorithmic',
name='Algorithmic',
description='Learn to imitate computations.',
)
add_group(
id='atari',
name='Atari',
description='Reach high scores in Atari 2600 games.',
)
add_group(
import os
from gym.scoreboard.registration import registry, add_task, add_group
add_group(id='gazebo', name='Gazebo', description='TODO.')
add_task(
id='test-v0',
group='gazebo',
summary='Obstacle avoidance in a Circuit.',
)
registry.finalize()
# Discover API key from the environment. (You should never have to
# change api_base / web_base.)
api_key = os.environ.get('OPENAI_GYM_API_KEY')
api_base = os.environ.get('OPENAI_GYM_API_BASE', 'https://gym-api.openai.com')
web_base = os.environ.get('OPENAI_GYM_WEB_BASE', 'https://gym.openai.com')
# The following controls how various tasks appear on the
# scoreboard. These registrations can differ from what's registered in
# this repository.
# groups
add_group(
id='classic_control',
name='Classic control',
description='Classic control problems from the RL literature.'
)
add_group(
id='algorithmic',
name='Algorithmic',
description='Learn to imitate computations.',
)
add_group(
id='atari',
name='Atari',
description='Reach high scores in Atari 2600 games.',
)
entry_point='{}_gym_doom:DoomTakeCoverEnv'.format(USERNAME),
max_episode_steps=10000,
reward_threshold=750.0,
)
register(
id='{}/DoomDeathmatch-v0'.format(USERNAME),
entry_point='{}_gym_doom:DoomDeathmatchEnv'.format(USERNAME),
max_episode_steps=10000,
reward_threshold=20.0,
)
# Scoreboard registration
# ==========================
add_group(id='doom',
name='Doom',
description='Doom environments based on VizDoom.')
add_task(id='{}/meta-Doom-v0'.format(USERNAME),
group='doom',
summary='Mission #1 to #9 - Beat all 9 Doom missions.',
description="""
This is a meta map that combines all 9 Doom levels.
Levels:
- #0 Doom Basic
- #1 Doom Corridor
- #2 Doom DefendCenter
- #3 Doom DefendLine
- #4 Doom HealthGathering
- #5 Doom MyWayHome
from gym.scoreboard.registration import add_task, add_group
add_group(id='bandits',
name='Bandits',
description='Various multi-armed Bandit environments')
add_task(
id='multi_arm_bandit_gaussian_fixed-v0',
group='bandits',
experimental=True,
contributor='bardofcodes',
summary=
"multi-armed bandit mentioned with reward based on a Gaussian distribution",
description="""
Each bandit gives a fixed reward,'r', where 'r' is sampled from a Gaussian Distribution(5,2)
""",
background="")
add_task(
id='multi_arm_bandit_gaussian_gaussian-v0',
group='bandits',
experimental=True,
contributor='bardofcodes',
summary=
"multi-armed bandit with each bandit having a normal distribution for reward distribution",
description="""
Each bandit has a N(r,1) reward distribution, where 'r' is sampled from a Normal(5,2) distribution.
""",
background="")
add_task(
level = (world_number - 1) * 4 + (level_number - 1)
register(
id='{}/SuperMarioBros-{}-{}{}-v0'.format(USERNAME, world_number, level_number, tile_suffix),
entry_point='{}_gym_super_mario:SuperMarioBrosEnv'.format(USERNAME),
max_episode_steps=10000,
reward_threshold=(max_distance - 40),
kwargs={ 'draw_tiles': draw_tiles, 'level': level },
# Seems to be non-deterministic about 5% of the time
nondeterministic=True,
)
# Scoreboard registration
# ==========================
add_group(
id= 'super-mario',
name= 'SuperMario',
description= '32 levels of the original Super Mario Bros game.'
)
add_task(
id='{}/meta-SuperMarioBros-v0'.format(USERNAME),
group='super-mario',
summary='Compilation of all 32 levels of Super Mario Bros. on Nintendo platform - Screen version.',
)
add_task(
id='{}/meta-SuperMarioBros-Tiles-v0'.format(USERNAME),
group='super-mario',
summary='Compilation of all 32 levels of Super Mario Bros. on Nintendo platform - Tiles version.',
)
for world in range(8):
)
register(
id='vladfi1/SSBM-headless-v0',
entry_point='dolphin:simpleSSBMEnv',
reward_threshold=1,
timestep_limit=9999999,
kwargs=dict(
cpu=9,
stage='battlefield',
),
nondeterministic=True,
)
# Scoreboard registration
# ==========================
add_group(
id= 'ssbm',
name= 'Super Smash Bros. Melee',
description= 'Beat the in-game AIs at SSBM.'
)
"""
add_task(
id='{}/meta-SuperMarioBros-v0'.format(USERNAME),
group='ssbm',
summary='Compilation of all 32 levels of Super Mario Bros. on Nintendo platform - Screen version.',
)
"""
# Discover API key from the environment. (You should never have to
# change api_base / web_base.)
api_key = os.environ.get('OPENAI_GYM_API_KEY')
api_base = os.environ.get('OPENAI_GYM_API_BASE', 'https://gym-api.openai.com')
web_base = os.environ.get('OPENAI_GYM_WEB_BASE', 'https://gym.openai.com')
# The following controls how various tasks appear on the
# scoreboard. These registrations can differ from what's registered in
# this repository.
# groups
add_group(
id='classic_control',
name='Classic control',
description='Classic control problems from the RL literature.'
)
add_group(
id='algorithmic',
name='Algorithmic',
description='Learn to imitate computations.',
)
add_group(
id='atari',
name='Atari',
description='Reach high scores in Atari 2600 games.',
)
import gym
from gym.envs.registration import register
from gym.scoreboard.registration import add_group
from gym.scoreboard.registration import add_taskcd
register(
id='SuperMarioBros-1-1-v0',
entry_point='gym.envs.ppaquette_gym_super_mario:MetaSuperMarioBrosEnv',
)
add_group(id='ppaquette_gym_super_mario',
name='ppaquette_gym_super_mario',
description='super_mario')
add_task(id='SuperMarioBros-1-1-v0',
group='ppaquette_gym_super_mario',
summary="SuperMarioBros-1-1-v0")
env = gym.make('SuperMarioBros-1-1-v0')
env.reset()
for _ in range(10000):
env.render()
env.step(env.action_space.sample()) # take a random action
from gym.scoreboard.registration import add_task, add_group
add_group(id='SpaceFortress',
name='SpaceFortress',
description='SpaceFortress games')
add_task(id='SpaceFortress-explode-image-v0',
summary="2D frictionless space shooter (explode, image)",
group='SpaceFortress',
contributor='Ryan M. Hope')
add_task(id='SpaceFortress-autoturn-image-v0',
summary="2D frictionless space shooter (autoturn, image)",
group='SpaceFortress',
contributor='Ryan M. Hope')
add_task(id='SpaceFortress-explode-features-v0',
summary="2D frictionless space shooter (explode, features)",
group='SpaceFortress',
contributor='Ryan M. Hope')
add_task(id='SpaceFortress-autoturn-features-v0',
summary="2D frictionless space shooter (autoturn, features)",
group='SpaceFortress',
contributor='Ryan M. Hope')
from gym.scoreboard.registration import registry, add_task, add_group
# Discover API key from the environment. (You should never have to
# change api_base / web_base.)
'''api_key = os.environ.get('OPENAI_GYM_API_KEY')
api_base = os.environ.get('OPENAI_GYM_API_BASE', 'https://gym-api.openai.com')
web_base = os.environ.get('OPENAI_GYM_WEB_BASE', 'https://gym.openai.com')'''
# The following controls how various tasks appear on the
# scoreboard. These registrations can differ from what's registered in
# this repository.
# groups
add_group(id='gym-vehicle', name='gym-vehicle', description='TODO.')
add_task(
id='GazeboCircuitLargeCatvehicleLidar-v0',
group='gym-vehicle',
summary='Test1.',
)
add_task(
id='GazeboCircuitLargeCatvehicleLidarNn-v0',
group='gym-vehicle',
summary='Test2.',
)
add_task(
id='GazeboTrackCatvehicleLidar-v0',
#tags={'wrapper_config.TimeLimit.max_episode_steps': 1818},
#timestep_limit=1818,
reward_threshold=16000)
register(
id='MinecraftHard-v0',
entry_point='gym_minecraft.envs:MinecraftEnv',
kwargs={'mission_file': 'hard.xml'},
#tags={'wrapper_config.TimeLimit.max_episode_steps': 2424},
#timestep_limit=2424,
reward_threshold=32000)
# Scoreboard registration
# ==========================
add_group(id='minecraft',
name='Minecraft',
description='Minecraft environments based on Malmo.')
add_task(id='MinecraftDefaultWorld1-v0',
group='minecraft',
summary='Survive and find gold, diamond or redstone!',
description="""
The agent appears in a default Minecraft world, with all possible objects.
The agent appears at x="-204" y="81" z="217", which depending on the world
that is generated means that it's going to fall initially to touch ground.
Goal:
The task instance is considered complete if the agent finds (mines) any
special block (any of "gold_block diamond_block redstone_block").
Rewards:
max_episode_steps=10000,
reward_threshold=20.0,
)
register(
id='{}/DoomBattle3-v0',
entry_point='{}.gym.doom:DoomBattleD3Env',
max_episode_steps=10000,
reward_threshold=20.0,
)
# Scoreboard registration
# ==========================
add_group(
id= 'doom',
name= 'Doom',
description= 'Doom environments based on VizDoom.'
)
add_task(
id='{}/meta-Doom-v0',
group='doom',
summary='Mission #1 to #9 - Beat all 9 Doom missions.',
description="""
This is a meta map that combines all 9 Doom levels.
Levels:
- #0 Doom Basic
- #1 Doom Corridor
- #2 Doom DefendCenter
- #3 Doom DefendLine
