| from easydict import EasyDict | |
| agent_num = 10 | |
| collector_env_num = 16 | |
| evaluator_env_num = 8 | |
| main_config = dict( | |
| exp_name='smac_MMM2_coma_seed0', | |
| env=dict( | |
| map_name='MMM2', | |
| difficulty=7, | |
| reward_only_positive=True, | |
| mirror_opponent=False, | |
| agent_num=agent_num, | |
| collector_env_num=collector_env_num, | |
| evaluator_env_num=evaluator_env_num, | |
| stop_value=0.999, | |
| n_evaluator_episode=32, | |
| manager=dict( | |
| shared_memory=False, | |
| reset_timeout=6000, | |
| ), | |
| ), | |
| policy=dict( | |
| model=dict( | |
| agent_num=agent_num, | |
| obs_shape=dict( | |
| agent_state=204, | |
| global_state=322, | |
| ), | |
| action_shape=18, | |
| actor_hidden_size_list=[64], | |
| ), | |
| learn=dict( | |
| update_per_collect=20, | |
| batch_size=32, | |
| learning_rate=0.0005, | |
| target_update_theta=0.001, | |
| discount_factor=0.99, | |
| td_lambda=0.9, | |
| policy_weight=0.001, | |
| value_weight=1, | |
| entropy_weight=0.01, | |
| ), | |
| collect=dict( | |
| n_episode=32, | |
| unroll_len=10, | |
| env_num=collector_env_num, | |
| ), | |
| eval=dict(env_num=evaluator_env_num, evaluator=dict(eval_freq=100, )), | |
| other=dict( | |
| eps=dict( | |
| type='exp', | |
| start=0.5, | |
| end=0.01, | |
| decay=200000, | |
| ), | |
| replay_buffer=dict( | |
| replay_buffer_size=5000, | |
| max_use=10, | |
| ), | |
| ), | |
| ), | |
| ) | |
| main_config = EasyDict(main_config) | |
| create_config = dict( | |
| env=dict( | |
| type='smac', | |
| import_names=['dizoo.smac.envs.smac_env'], | |
| ), | |
| env_manager=dict(type='subprocess'), | |
| policy=dict(type='coma'), | |
| collector=dict(type='episode', get_train_sample=True), | |
| ) | |
| create_config = EasyDict(create_config) | |
| if __name__ == '__main__': | |
| from ding.entry import serial_pipeline | |
| serial_pipeline((main_config, create_config), seed=0) | |