qmix_config.py

#   Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
QMixConfig:
    'scenario': (str) The scenario in smac environments. All senarios: ['3m',
        '8m', '25m', '5m_vs_6m', '8m_vs_9m', '10m_vs_11m', '27m_vs_39m',
        'MMM', 'MMM2', '2s3z', '3s5z', '3s5z_vs_3s6z', '3s_vs_3z',
        '3s_vs_4z', '3s_vs_5z', '1c3s5z', '2m_vs_1z', 'corridor',
        '6h_vs_8z', '2s_vs_1sc', 'so_many_baneling', 'bane_vs_bane',
        '2c_vs_64zg']
    'replay_buffer_size': (int) Max episode number to be stored in the replay buffer.
    'mixing_embed_dim': (int) Embed dim of the mixing network.
    'rnn_hidden_dim': (int) Dim of GRU's hidden state.
    'memory_warmup_size': (int) The learning process will not start untill current
        replay buffer size >= 'memory_warmup_size'.
    'gamma': (float) Discount factor in reinforcement learning.
    'exploration_start': (float) Initial 'epsilon' in epsilon-greedy based exploration.
    'min_exploration': (float) Min 'epsilon' in epsilon-greedy.
    'update_target_interval': (int) Synchronize paramters to the target model after
        the model has been learned 'update_target_interval' times.
    'batch_size': (int) Training batch_size.
    'training_steps': (int) Total steps for training.
    'test_steps': (int) Evaluate the model every 'test_steps' steps.
    'clip_grad_norm': (float) clipped value of global norm of gradients.
    'hypernet_layers': (int; 1 or 2) Number of layers in hypernetwork.
    'hypernet_embed_dim' (int, only make sense when 'hypernet_layers'==2)
    'double_q' (bool, True or False) Double-DQN.
    'difficulty': (str) Difficulty of the environment. Max Value: "7" (very difficult)
"""

QMixConfig = {
    'master_address': 'localhost:8010',
    'actor_num': 2,
    'env_num': 2,
    'sample_batch_episode': 4,
    'log_metrics_interval_s': 1,
    'calc_num': 8,
    'scenario': '1c3s5z',
    'replay_buffer_size': 5000,
    'mixing_embed_dim': 32,
    'rnn_hidden_dim': 64,
    'lr': 0.0005,
    'memory_warmup_size': 16,
    'gamma': 0.99,
    'exploration_start': 1.0,
    'min_exploration': 0.1,
    'exploration_decay': 2e-6,
    'update_target_interval': 50,
    'batch_size': 16,
    'training_steps': 5000,
    'test_steps': 100,
    'clip_grad_norm': 10,
    'hypernet_layers': 2,
    'hypernet_embed_dim': 64,
    'double_q': True,
    'difficulty': '7'
}