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config.py
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config.py
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from collections import namedtuple
Game = namedtuple('Game', ['env_name', 'time_factor', 'input_size', 'output_size', 'layers', 'activation', 'noise_bias', 'output_noise', 'rnn_mode'])
games = {}
slimevolley = Game(env_name='SlimeVolley',
input_size=12,
output_size=3,
time_factor=0,
layers=[20, 20],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['slimevolley'] = slimevolley
cartpole_swingup = Game(env_name='CartPoleSwingUp',
input_size=5,
output_size=1,
time_factor=0,
layers=[10, 0],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['cartpole_swingup'] = cartpole_swingup
bullet_cartpole = Game(env_name='CartPoleContinuousBulletEnv-v0',
input_size=4,
output_size=1,
time_factor=200,
layers=[25, 5],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_cartpole'] = bullet_cartpole
bullet_pendulum = Game(env_name='InvertedPendulumSwingupBulletEnv-v0',
input_size=5,
output_size=1,
time_factor=1000,
layers=[25, 5],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_pendulum'] = bullet_pendulum
bullet_double_pendulum = Game(env_name='InvertedDoublePendulumBulletEnv-v0',
input_size=9,
output_size=1,
time_factor=0,
layers=[45, 5],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_double_pendulum'] = bullet_double_pendulum
bullet_minitaur_duck = Game(env_name='MinitaurDuckBulletEnv-v0',
input_size=28,
output_size=8,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_minitaur_duck'] = bullet_minitaur_duck
bullet_minitaur_duck = Game(env_name='MinitaurDuckBulletEnv-v0',
input_size=28,
output_size=8,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_minitaur_duck'] = bullet_minitaur_duck
bullet_kuka_grasping = Game(env_name='KukaBulletEnv-v0',
input_size=9,
output_size=3,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_kuka_grasping'] = bullet_kuka_grasping
bullet_kuka_grasping_stoc = Game(env_name='KukaBulletEnv-v0',
input_size=9,
output_size=3,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_kuka_grasping_stoc'] = bullet_kuka_grasping_stoc
bullet_minitaur_duck_stoc = Game(env_name='MinitaurDuckBulletEnv-v0',
input_size=28,
output_size=8,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=-1.0,
output_noise=[True, True, True],
rnn_mode=False,
)
games['bullet_minitaur_duck_stoc'] = bullet_minitaur_duck_stoc
bullet_minitaur_ball = Game(env_name='MinitaurBallBulletEnv-v0',
input_size=28,
output_size=8,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_minitaur_ball'] = bullet_minitaur_ball
bullet_minitaur_ball_stoc = Game(env_name='MinitaurBallBulletEnv-v0',
input_size=28,
output_size=8,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=-1.0,
output_noise=[True, True, True],
rnn_mode=False,
)
games['bullet_minitaur_ball_stoc'] = bullet_minitaur_ball_stoc
bullet_half_cheetah = Game(env_name='HalfCheetahBulletEnv-v0',
input_size=26,
output_size=6,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_half_cheetah'] = bullet_half_cheetah
bullet_humanoid = Game(env_name='HumanoidBulletEnv-v0',
input_size=44,
output_size=17,
layers=[220, 85],
time_factor=1000,
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_humanoid'] = bullet_humanoid
bullet_ant = Game(env_name='AntBulletEnv-v0',
input_size=28,
output_size=8,
layers=[64, 32],
time_factor=1000,
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_ant'] = bullet_ant
bullet_ant_deterministic = Game(env_name='AntBulletEnv-v0',
input_size=28,
output_size=8,
layers=[32, 16],
time_factor=1000,
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_ant_deterministic'] = bullet_ant_deterministic
bullet_ant_tiny = Game(env_name='AntBulletEnv-v0',
input_size=28,
output_size=8,
layers=[16, 0],
time_factor=1000,
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_ant_tiny'] = bullet_ant_tiny
bullet_ant_custom = Game(env_name='NoDeathAntBulletEnv-v0',
input_size=28,
output_size=8,
layers=[16, 0],
time_factor=0,
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_ant_custom'] = bullet_ant_custom
bullet_walker = Game(env_name='Walker2DBulletEnv-v0',
input_size=22,
output_size=6,
time_factor=1000,
layers=[110, 30],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_walker'] = bullet_walker
bullet_hopper = Game(env_name='HopperBulletEnv-v0',
input_size=15,
output_size=3,
layers=[75, 15],
time_factor=1000,
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['bullet_hopper'] = bullet_hopper
bullet_racecar = Game(env_name='RacecarBulletEnv-v0',
input_size=2,
output_size=2,
time_factor=1000,
layers=[20, 20],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_racecar'] = bullet_racecar
bullet_minitaur = Game(env_name='MinitaurBulletEnv-v0',
input_size=28,
output_size=8,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bullet_minitaur'] = bullet_minitaur
bullet_minitaur_stoc = Game(env_name='MinitaurBulletEnv-v0',
input_size=28,
output_size=8,
time_factor=0,
layers=[64, 32],
activation='tanh',
noise_bias=0.0,
output_noise=[True, True, True],
rnn_mode=False,
)
games['bullet_minitaur_stoc'] = bullet_minitaur_stoc
bipedhard_stoc = Game(env_name='BipedalWalkerHardcore-v2',
input_size=24,
output_size=4,
time_factor=1000,
layers=[120, 20],
activation='passthru',
noise_bias=0.0,
output_noise=[True, True, True],
rnn_mode=False,
)
games['bipedhard_stoc'] = bipedhard_stoc
bipedhard = Game(env_name='BipedalWalkerHardcore-v2',
input_size=24,
output_size=4,
time_factor=0,
layers=[40, 40],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['bipedhard'] = bipedhard
biped = Game(env_name='BipedalWalker-v2',
input_size=24,
output_size=4,
time_factor=0,
layers=[40, 40],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, False],
rnn_mode=False,
)
games['biped'] = biped
rocketlander = Game(env_name='RocketLander-v0',
input_size=8,
output_size=3,
time_factor=0,
layers=[32, 16],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['rocketlander'] = rocketlander
carracing = Game(env_name='CarRacing-v0',
input_size=64,
output_size=3,
time_factor=0,
layers=[40, 40],
activation='tanh',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['carracing'] = carracing
osimrun = Game(env_name='osimrun',
input_size=41,
output_size=18,
time_factor=1000,
layers=[205, 90],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['osimrun'] = osimrun
robo_reacher = Game(env_name='RoboschoolReacher-v1',
input_size=9,
output_size=2,
layers=[45, 10],
time_factor=1000,
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_reacher'] = robo_reacher
robo_flagrun = Game(env_name='RoboschoolHumanoidFlagrunHarder-v1',
input_size=44,
output_size=17,
layers=[220, 85],
time_factor=1000,
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_flagrun'] = robo_flagrun
robo_pendulum = Game(env_name='RoboschoolInvertedPendulumSwingup-v1',
input_size=5,
output_size=1,
time_factor=1000,
layers=[25, 5],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_pendulum'] = robo_pendulum
robo_double_pendulum = Game(env_name='RoboschoolInvertedDoublePendulum-v1',
input_size=9,
output_size=1,
time_factor=0,
layers=[45, 5],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_double_pendulum'] = robo_double_pendulum
robo_humanoid = Game(env_name='RoboschoolHumanoid-v1',
input_size=44,
output_size=17,
layers=[220, 85],
time_factor=1000,
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_humanoid'] = robo_humanoid
robo_ant = Game(env_name='RoboschoolAnt-v1',
input_size=28,
output_size=8,
layers=[140, 40],
time_factor=1000,
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_ant'] = robo_ant
robo_walker= Game(env_name='RoboschoolWalker2d-v1',
input_size=22,
output_size=6,
time_factor=1000,
layers=[110, 30],
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_walker'] = robo_walker
robo_hopper = Game(env_name='RoboschoolHopper-v1',
input_size=15,
output_size=3,
layers=[75, 15],
time_factor=1000,
activation='passthru',
noise_bias=0.0,
output_noise=[False, False, True],
rnn_mode=False,
)
games['robo_hopper'] = robo_hopper