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CartPole-v1: &cartpole-defaults
n_timesteps: !!float 1e5
env_hyperparams:
n_envs: 8
algo_hyperparams:
n_steps: 32
batch_size: 256
n_epochs: 20
gae_lambda: 0.8
gamma: 0.98
ent_coef: 0.0
learning_rate: 0.001
learning_rate_decay: linear
clip_range: 0.2
clip_range_decay: linear
eval_hyperparams:
step_freq: !!float 2.5e4
CartPole-v0:
<<: *cartpole-defaults
n_timesteps: !!float 5e4
MountainCar-v0:
n_timesteps: !!float 1e6
env_hyperparams:
normalize: true
n_envs: 16
algo_hyperparams:
n_steps: 16
n_epochs: 4
gae_lambda: 0.98
gamma: 0.99
ent_coef: 0.0
MountainCarContinuous-v0:
n_timesteps: !!float 1e5
env_hyperparams:
normalize: true
n_envs: 4
# policy_hyperparams:
# init_layers_orthogonal: false
# log_std_init: -3.29
# use_sde: true
algo_hyperparams:
n_steps: 512
batch_size: 256
n_epochs: 10
learning_rate: !!float 7.77e-5
ent_coef: 0.01 # 0.00429
ent_coef_decay: linear
clip_range: 0.1
gae_lambda: 0.9
max_grad_norm: 5
vf_coef: 0.19
eval_hyperparams:
step_freq: 5000
Acrobot-v1:
n_timesteps: !!float 1e6
env_hyperparams:
n_envs: 16
normalize: true
algo_hyperparams:
n_steps: 256
n_epochs: 4
gae_lambda: 0.94
gamma: 0.99
ent_coef: 0.0
LunarLander-v2:
n_timesteps: !!float 4e6
env_hyperparams:
n_envs: 16
algo_hyperparams:
n_steps: 1024
batch_size: 64
n_epochs: 4
gae_lambda: 0.98
gamma: 0.999
learning_rate: !!float 5e-4
learning_rate_decay: linear
clip_range: 0.2
clip_range_decay: linear
ent_coef: 0.01
normalize_advantage: false
BipedalWalker-v3:
n_timesteps: !!float 10e6
env_hyperparams:
n_envs: 16
normalize: true
algo_hyperparams:
n_steps: 2048
batch_size: 64
gae_lambda: 0.95
gamma: 0.99
n_epochs: 10
ent_coef: 0.001
learning_rate: !!float 2.5e-4
learning_rate_decay: linear
clip_range: 0.2
clip_range_decay: linear
CarRacing-v0: &carracing-defaults
n_timesteps: !!float 4e6
env_hyperparams:
n_envs: 8
frame_stack: 4
policy_hyperparams: &carracing-policy-defaults
use_sde: true
log_std_init: -2
init_layers_orthogonal: false
activation_fn: relu
share_features_extractor: false
cnn_flatten_dim: 256
hidden_sizes: [256]
algo_hyperparams:
n_steps: 512
batch_size: 128
n_epochs: 10
learning_rate: !!float 1e-4
learning_rate_decay: linear
gamma: 0.99
gae_lambda: 0.95
ent_coef: 0.0
sde_sample_freq: 4
max_grad_norm: 0.5
vf_coef: 0.5
clip_range: 0.2
impala-CarRacing-v0:
<<: *carracing-defaults
env_id: CarRacing-v0
policy_hyperparams:
<<: *carracing-policy-defaults
cnn_style: impala
init_layers_orthogonal: true
cnn_layers_init_orthogonal: false
hidden_sizes: []
# BreakoutNoFrameskip-v4
# PongNoFrameskip-v4
# SpaceInvadersNoFrameskip-v4
# QbertNoFrameskip-v4
_atari: &atari-defaults
n_timesteps: !!float 1e7
env_hyperparams: &atari-env-defaults
n_envs: 8
frame_stack: 4
no_reward_timeout_steps: 1000
no_reward_fire_steps: 500
vec_env_class: async
policy_hyperparams: &atari-policy-defaults
activation_fn: relu
algo_hyperparams: &atari-algo-defaults
n_steps: 128
batch_size: 256
n_epochs: 4
learning_rate: !!float 2.5e-4
learning_rate_decay: linear
clip_range: 0.1
clip_range_decay: linear
vf_coef: 0.5
ent_coef: 0.01
eval_hyperparams:
deterministic: false
_norm-rewards-atari: &norm-rewards-atari-default
<<: *atari-defaults
env_hyperparams:
<<: *atari-env-defaults
clip_atari_rewards: false
normalize: true
normalize_kwargs:
norm_obs: false
norm_reward: true
norm-rewards-BreakoutNoFrameskip-v4:
<<: *norm-rewards-atari-default
env_id: BreakoutNoFrameskip-v4
debug-PongNoFrameskip-v4:
<<: *atari-defaults
device: cpu
env_id: PongNoFrameskip-v4
env_hyperparams:
<<: *atari-env-defaults
vec_env_class: sync
_impala-atari: &impala-atari-defaults
<<: *atari-defaults
policy_hyperparams:
<<: *atari-policy-defaults
cnn_style: impala
cnn_flatten_dim: 256
init_layers_orthogonal: true
cnn_layers_init_orthogonal: false
impala-PongNoFrameskip-v4:
<<: *impala-atari-defaults
env_id: PongNoFrameskip-v4
impala-BreakoutNoFrameskip-v4:
<<: *impala-atari-defaults
env_id: BreakoutNoFrameskip-v4
impala-SpaceInvadersNoFrameskip-v4:
<<: *impala-atari-defaults
env_id: SpaceInvadersNoFrameskip-v4
impala-QbertNoFrameskip-v4:
<<: *impala-atari-defaults
env_id: QbertNoFrameskip-v4
_microrts: µrts-defaults
<<: *atari-defaults
n_timesteps: !!float 2e6
env_hyperparams: µrts-env-defaults
n_envs: 8
vec_env_class: sync
mask_actions: true
policy_hyperparams: µrts-policy-defaults
<<: *atari-policy-defaults
cnn_style: microrts
cnn_flatten_dim: 128
algo_hyperparams: µrts-algo-defaults
<<: *atari-algo-defaults
clip_range_decay: none
clip_range_vf: 0.1
ppo2_vf_coef_halving: true
eval_hyperparams: µrts-eval-defaults
deterministic: false # Good idea because MultiCategorical mode isn't great
_no-mask-microrts: &no-mask-microrts-defaults
<<: *microrts-defaults
env_hyperparams:
<<: *microrts-env-defaults
mask_actions: false
MicrortsMining-v1-NoMask:
<<: *no-mask-microrts-defaults
env_id: MicrortsMining-v1
MicrortsAttackShapedReward-v1-NoMask:
<<: *no-mask-microrts-defaults
env_id: MicrortsAttackShapedReward-v1
MicrortsRandomEnemyShapedReward3-v1-NoMask:
<<: *no-mask-microrts-defaults
env_id: MicrortsRandomEnemyShapedReward3-v1
_microrts_ai: µrts-ai-defaults
<<: *microrts-defaults
n_timesteps: !!float 100e6
additional_keys_to_log: ["microrts_stats", "microrts_results"]
env_hyperparams: µrts-ai-env-defaults
n_envs: 24
env_type: microrts
make_kwargs: µrts-ai-env-make-kwargs-defaults
num_selfplay_envs: 0
max_steps: 4000
render_theme: 2
map_paths: [maps/16x16/basesWorkers16x16.xml]
reward_weight: [10.0, 1.0, 1.0, 0.2, 1.0, 4.0]
policy_hyperparams: µrts-ai-policy-defaults
<<: *microrts-policy-defaults
cnn_flatten_dim: 256
actor_head_style: gridnet
algo_hyperparams: µrts-ai-algo-defaults
<<: *microrts-algo-defaults
learning_rate: !!float 2.5e-4
learning_rate_decay: linear
n_steps: 512
batch_size: 3072
n_epochs: 4
ent_coef: 0.01
vf_coef: 0.5
max_grad_norm: 0.5
clip_range: 0.1
clip_range_vf: 0.1
eval_hyperparams: µrts-ai-eval-defaults
<<: *microrts-eval-defaults
score_function: mean
max_video_length: 4000
env_overrides: µrts-ai-eval-env-overrides
make_kwargs:
<<: *microrts-ai-env-make-kwargs-defaults
max_steps: 4000
reward_weight: [1.0, 0, 0, 0, 0, 0]
MicrortsAttackPassiveEnemySparseReward-v3:
<<: *microrts-ai-defaults
n_timesteps: !!float 2e6
env_id: MicrortsAttackPassiveEnemySparseReward-v3 # Workaround to keep model name simple
env_hyperparams:
<<: *microrts-ai-env-defaults
bots:
passiveAI: 24
MicrortsDefeatRandomEnemySparseReward-v3: µrts-random-ai-defaults
<<: *microrts-ai-defaults
n_timesteps: !!float 2e6
env_id: MicrortsDefeatRandomEnemySparseReward-v3 # Workaround to keep model name simple
env_hyperparams:
<<: *microrts-ai-env-defaults
bots:
randomBiasedAI: 24
enc-dec-MicrortsDefeatRandomEnemySparseReward-v3:
<<: *microrts-random-ai-defaults
policy_hyperparams:
<<: *microrts-ai-policy-defaults
cnn_style: gridnet_encoder
actor_head_style: gridnet_decoder
v_hidden_sizes: [128]
unet-MicrortsDefeatRandomEnemySparseReward-v3:
<<: *microrts-random-ai-defaults
# device: cpu
policy_hyperparams:
<<: *microrts-ai-policy-defaults
actor_head_style: unet
v_hidden_sizes: [256, 128]
algo_hyperparams:
<<: *microrts-ai-algo-defaults
learning_rate: !!float 2.5e-4
learning_rate_decay: spike
MicrortsDefeatCoacAIShaped-v3: µrts-coacai-defaults
<<: *microrts-ai-defaults
env_id: MicrortsDefeatCoacAIShaped-v3 # Workaround to keep model name simple
n_timesteps: !!float 300e6
env_hyperparams: µrts-coacai-env-defaults
<<: *microrts-ai-env-defaults
bots:
coacAI: 24
eval_hyperparams: µrts-coacai-eval-defaults
<<: *microrts-ai-eval-defaults
step_freq: !!float 1e6
n_episodes: 26
env_overrides: µrts-coacai-eval-env-overrides
<<: *microrts-ai-eval-env-overrides
n_envs: 26
bots:
coacAI: 2
randomBiasedAI: 2
randomAI: 2
passiveAI: 2
workerRushAI: 2
lightRushAI: 2
naiveMCTSAI: 2
mixedBot: 2
rojo: 2
izanagi: 2
tiamat: 2
droplet: 2
guidedRojoA3N: 2
MicrortsDefeatCoacAIShaped-v3-diverseBots: µrts-diverse-defaults
<<: *microrts-coacai-defaults
env_hyperparams:
<<: *microrts-coacai-env-defaults
bots:
coacAI: 18
randomBiasedAI: 2
lightRushAI: 2
workerRushAI: 2
enc-dec-MicrortsDefeatCoacAIShaped-v3-diverseBots:
µrts-env-dec-diverse-defaults
<<: *microrts-diverse-defaults
policy_hyperparams:
<<: *microrts-ai-policy-defaults
cnn_style: gridnet_encoder
actor_head_style: gridnet_decoder
v_hidden_sizes: [128]
debug-enc-dec-MicrortsDefeatCoacAIShaped-v3-diverseBots:
<<: *microrts-env-dec-diverse-defaults
n_timesteps: !!float 1e6
unet-MicrortsDefeatCoacAIShaped-v3-diverseBots: µrts-unet-defaults
<<: *microrts-diverse-defaults
policy_hyperparams:
<<: *microrts-ai-policy-defaults
actor_head_style: unet
v_hidden_sizes: [256, 128]
algo_hyperparams: µrts-unet-algo-defaults
<<: *microrts-ai-algo-defaults
learning_rate: !!float 2.5e-4
learning_rate_decay: spike
Microrts-selfplay-unet: µrts-selfplay-defaults
<<: *microrts-unet-defaults
env_hyperparams: µrts-selfplay-env-defaults
<<: *microrts-ai-env-defaults
make_kwargs: µrts-selfplay-env-make-kwargs-defaults
<<: *microrts-ai-env-make-kwargs-defaults
num_selfplay_envs: 36
self_play_kwargs:
num_old_policies: 12
save_steps: 300000
swap_steps: 6000
swap_window_size: 4
window: 33
eval_hyperparams: µrts-selfplay-eval-defaults
<<: *microrts-coacai-eval-defaults
env_overrides: µrts-selfplay-eval-env-overrides
<<: *microrts-coacai-eval-env-overrides
self_play_kwargs: {}
Microrts-selfplay-unet-winloss: µrts-selfplay-winloss-defaults
<<: *microrts-selfplay-defaults
env_hyperparams:
<<: *microrts-selfplay-env-defaults
make_kwargs:
<<: *microrts-selfplay-env-make-kwargs-defaults
reward_weight: [1.0, 0, 0, 0, 0, 0]
algo_hyperparams: µrts-selfplay-winloss-algo-defaults
<<: *microrts-unet-algo-defaults
gamma: 0.999
Microrts-selfplay-unet-decay: µrts-selfplay-decay-defaults
<<: *microrts-selfplay-defaults
microrts_reward_decay_callback: true
algo_hyperparams:
<<: *microrts-unet-algo-defaults
gamma_end: 0.999
Microrts-selfplay-unet-debug: µrts-selfplay-debug-defaults
<<: *microrts-selfplay-decay-defaults
eval_hyperparams:
<<: *microrts-selfplay-eval-defaults
step_freq: !!float 1e5
env_overrides:
<<: *microrts-selfplay-eval-env-overrides
n_envs: 24
bots:
coacAI: 12
randomBiasedAI: 4
workerRushAI: 4
lightRushAI: 4
Microrts-selfplay-unet-debug-mps:
<<: *microrts-selfplay-debug-defaults
device: mps
HalfCheetahBulletEnv-v0: &pybullet-defaults
n_timesteps: !!float 2e6
env_hyperparams: &pybullet-env-defaults
n_envs: 16
normalize: true
policy_hyperparams: &pybullet-policy-defaults
pi_hidden_sizes: [256, 256]
v_hidden_sizes: [256, 256]
activation_fn: relu
algo_hyperparams: &pybullet-algo-defaults
n_steps: 512
batch_size: 128
n_epochs: 20
gamma: 0.99
gae_lambda: 0.9
ent_coef: 0.0
max_grad_norm: 0.5
vf_coef: 0.5
learning_rate: !!float 3e-5
clip_range: 0.4
AntBulletEnv-v0:
<<: *pybullet-defaults
policy_hyperparams:
<<: *pybullet-policy-defaults
algo_hyperparams:
<<: *pybullet-algo-defaults
Walker2DBulletEnv-v0:
<<: *pybullet-defaults
algo_hyperparams:
<<: *pybullet-algo-defaults
clip_range_decay: linear
HopperBulletEnv-v0:
<<: *pybullet-defaults
algo_hyperparams:
<<: *pybullet-algo-defaults
clip_range_decay: linear
HumanoidBulletEnv-v0:
<<: *pybullet-defaults
n_timesteps: !!float 1e7
env_hyperparams:
<<: *pybullet-env-defaults
n_envs: 8
policy_hyperparams:
<<: *pybullet-policy-defaults
# log_std_init: -1
algo_hyperparams:
<<: *pybullet-algo-defaults
n_steps: 2048
batch_size: 64
n_epochs: 10
gae_lambda: 0.95
learning_rate: !!float 2.5e-4
clip_range: 0.2
_procgen: &procgen-defaults
env_hyperparams: &procgen-env-defaults
env_type: procgen
n_envs: 64
# grayscale: false
# frame_stack: 4
normalize: true # procgen only normalizes reward
make_kwargs: &procgen-make-kwargs-defaults
num_threads: 8
policy_hyperparams: &procgen-policy-defaults
activation_fn: relu
cnn_style: impala
cnn_flatten_dim: 256
init_layers_orthogonal: true
cnn_layers_init_orthogonal: false
algo_hyperparams: &procgen-algo-defaults
gamma: 0.999
gae_lambda: 0.95
n_steps: 256
batch_size: 2048
n_epochs: 3
ent_coef: 0.01
clip_range: 0.2
# clip_range_decay: linear
clip_range_vf: 0.2
learning_rate: !!float 5e-4
# learning_rate_decay: linear
vf_coef: 0.5
eval_hyperparams: &procgen-eval-defaults
ignore_first_episode: true
# deterministic: false
step_freq: !!float 1e5
_procgen-easy: &procgen-easy-defaults
<<: *procgen-defaults
n_timesteps: !!float 25e6
env_hyperparams: &procgen-easy-env-defaults
<<: *procgen-env-defaults
make_kwargs:
<<: *procgen-make-kwargs-defaults
distribution_mode: easy
procgen-coinrun-easy: &coinrun-easy-defaults
<<: *procgen-easy-defaults
env_id: coinrun
debug-procgen-coinrun:
<<: *coinrun-easy-defaults
device: cpu
procgen-starpilot-easy:
<<: *procgen-easy-defaults
env_id: starpilot
procgen-bossfight-easy:
<<: *procgen-easy-defaults
env_id: bossfight
procgen-bigfish-easy:
<<: *procgen-easy-defaults
env_id: bigfish
_procgen-hard: &procgen-hard-defaults
<<: *procgen-defaults
n_timesteps: !!float 200e6
env_hyperparams: &procgen-hard-env-defaults
<<: *procgen-env-defaults
n_envs: 256
make_kwargs:
<<: *procgen-make-kwargs-defaults
distribution_mode: hard
algo_hyperparams: &procgen-hard-algo-defaults
<<: *procgen-algo-defaults
batch_size: 8192
clip_range_decay: linear
learning_rate_decay: linear
eval_hyperparams:
<<: *procgen-eval-defaults
step_freq: !!float 5e5
procgen-starpilot-hard: &procgen-starpilot-hard-defaults
<<: *procgen-hard-defaults
env_id: starpilot
procgen-starpilot-hard-2xIMPALA:
<<: *procgen-starpilot-hard-defaults
policy_hyperparams:
<<: *procgen-policy-defaults
impala_channels: [32, 64, 64]
algo_hyperparams:
<<: *procgen-hard-algo-defaults
learning_rate: !!float 3.3e-4
procgen-starpilot-hard-2xIMPALA-fat:
<<: *procgen-starpilot-hard-defaults
policy_hyperparams:
<<: *procgen-policy-defaults
impala_channels: [32, 64, 64]
cnn_flatten_dim: 512
algo_hyperparams:
<<: *procgen-hard-algo-defaults
learning_rate: !!float 2.5e-4
procgen-starpilot-hard-4xIMPALA:
<<: *procgen-starpilot-hard-defaults
policy_hyperparams:
<<: *procgen-policy-defaults
impala_channels: [64, 128, 128]
algo_hyperparams:
<<: *procgen-hard-algo-defaults
learning_rate: !!float 2.1e-4
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