Pendulum-v1-EfficientZero / policy_config.py
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exp_config = {
'main_config': {
'exp_name': 'Pendulum-v1-EfficientZero',
'seed': 0,
'env': {
'env_id': 'Pendulum-v1',
'continuous': False,
'manually_discretization': True,
'each_dim_disc_size': 11,
'collector_env_num': 8,
'evaluator_env_num': 3,
'n_evaluator_episode': 3,
'manager': {
'shared_memory': False
}
},
'policy': {
'on_policy': False,
'cuda': True,
'multi_gpu': False,
'bp_update_sync': True,
'traj_len_inf': False,
'model': {
'observation_shape': 3,
'action_space_size': 11,
'model_type': 'mlp',
'lstm_hidden_size': 128,
'latent_state_dim': 128
},
'use_rnd_model': False,
'sampled_algo': False,
'gumbel_algo': False,
'mcts_ctree': True,
'collector_env_num': 8,
'evaluator_env_num': 3,
'env_type': 'not_board_games',
'action_type': 'fixed_action_space',
'battle_mode': 'play_with_bot_mode',
'monitor_extra_statistics': True,
'game_segment_length': 50,
'transform2string': False,
'gray_scale': False,
'use_augmentation': False,
'augmentation': ['shift', 'intensity'],
'ignore_done': False,
'update_per_collect': 200,
'model_update_ratio': 0.1,
'batch_size': 256,
'optim_type': 'Adam',
'learning_rate': 0.003,
'target_update_freq': 100,
'target_update_freq_for_intrinsic_reward': 1000,
'weight_decay': 0.0001,
'momentum': 0.9,
'grad_clip_value': 10,
'n_episode': 8,
'num_simulations': 50,
'discount_factor': 0.997,
'td_steps': 5,
'num_unroll_steps': 5,
'reward_loss_weight': 1,
'value_loss_weight': 0.25,
'policy_loss_weight': 1,
'policy_entropy_loss_weight': 0,
'ssl_loss_weight': 2,
'lr_piecewise_constant_decay': False,
'threshold_training_steps_for_final_lr': 50000,
'manual_temperature_decay': False,
'threshold_training_steps_for_final_temperature': 100000,
'fixed_temperature_value': 0.25,
'use_ture_chance_label_in_chance_encoder': False,
'use_priority': True,
'priority_prob_alpha': 0.6,
'priority_prob_beta': 0.4,
'root_dirichlet_alpha': 0.3,
'root_noise_weight': 0.25,
'random_collect_episode_num': 0,
'eps': {
'eps_greedy_exploration_in_collect': False,
'type': 'linear',
'start': 1.0,
'end': 0.05,
'decay': 100000
},
'cfg_type': 'EfficientZeroPolicyDict',
'lstm_horizon_len': 5,
'reanalyze_ratio': 0,
'eval_freq': 2000,
'replay_buffer_size': 1000000
},
'wandb_logger': {
'gradient_logger': False,
'video_logger': False,
'plot_logger': False,
'action_logger': False,
'return_logger': False
}
},
'create_config': {
'env': {
'type':
'pendulum_lightzero',
'import_names':
['zoo.classic_control.pendulum.envs.pendulum_lightzero_env']
},
'env_manager': {
'type': 'subprocess'
},
'policy': {
'type': 'efficientzero',
'import_names': ['lzero.policy.efficientzero']
}
}
}