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from easydict import EasyDict
agent_num = 3
obs_dim = 26
collector_env_num = 8
evaluator_env_num = 32
main_config = dict(
exp_name='gfootball_keeper_mappo_seed0',
env=dict(
env_name='academy_3_vs_1_with_keeper',
agent_num=agent_num,
obs_dim=obs_dim,
n_evaluator_episode=32,
stop_value=1,
collector_env_num=collector_env_num,
evaluator_env_num=evaluator_env_num,
manager=dict(
shared_memory=False,
reset_timeout=6000,
),
),
policy=dict(
cuda=True,
multi_agent=True,
model=dict(
# (int) obs_shape: The shapeof observation of each agent.
# (int) global_obs_shape: The shape of global observation.
agent_obs_shape=obs_dim,
global_obs_shape=int(obs_dim * 2),
# (int) action_shape: The number of action which each agent can take.
action_shape=19,
),
learn=dict(
epoch_per_collect=10,
batch_size=3200,
learning_rate=5e-4,
# ==============================================================
# The following configs is algorithm-specific
# ==============================================================
# (float) The loss weight of value network, policy network weight is set to 1
value_weight=0.5,
# (float) The loss weight of entropy regularization, policy network weight is set to 1
entropy_weight=0.01,
# (float) PPO clip ratio, defaults to 0.2
clip_ratio=0.05,
# (bool) Whether to use advantage norm in a whole training batch
adv_norm=False,
value_norm=True,
ppo_param_init=True,
grad_clip_type='clip_norm',
grad_clip_value=10,
ignore_done=False,
),
collect=dict(env_num=collector_env_num, n_sample=3200),
eval=dict(env_num=evaluator_env_num, evaluator=dict(eval_freq=50, )),
),
)
main_config = EasyDict(main_config)
create_config = dict(
env=dict(
type='gfootball-academy',
import_names=['dizoo.gfootball.envs.gfootball_academy_env'],
),
env_manager=dict(type='subprocess'),
policy=dict(type='ppo'),
)
create_config = EasyDict(create_config)
if __name__ == "__main__":
# or you can enter `ding -m serial_onpolicy -c gfootball_keeper_mappo_config.py -s 0`
from ding.entry import serial_pipeline_onpolicy
serial_pipeline_onpolicy([main_config, create_config], seed=0)
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