gfootball

xuance/configs/mappo/football/3v1.yaml

@@ -20,24 +20,24 @@ runner: "Football_Runner"
 use_recurrent: True
 rnn: "GRU"
 recurrent_layer_N: 1
-fc_hidden_sizes: [64, 64, 64]
+fc_hidden_sizes: [64]
 recurrent_hidden_size: 64
 N_recurrent_layers: 1
 dropout: 0
 normalize: "LayerNorm"
 initialize: "orthogonal"
 gain: 0.01
 
-actor_hidden_size: []
-critic_hidden_size: []
+actor_hidden_size: [64, 64]
+critic_hidden_size: [64, 64]
 activation: "ReLU"
 
 seed: 1
 parallels: 50
 n_size: 200
 n_epoch: 15
 n_minibatch: 2
-learning_rate: 0.0007  # 7e-4
+learning_rate: 0.0005  # 5e-4
 weight_decay: 0
 
 vf_coef: 1.0

xuance/configs/mappo/sc2/5m_vs_6m.yaml

@@ -12,16 +12,16 @@ on_policy: True
 use_recurrent: True
 rnn: "GRU"
 recurrent_layer_N: 1
-fc_hidden_sizes: [64, 64, 64]
+fc_hidden_sizes: [64]
 recurrent_hidden_size: 64
 N_recurrent_layers: 1
 dropout: 0
 normalize: "LayerNorm"
 initialize: "orthogonal"
 gain: 0.01
 
-actor_hidden_size: []
-critic_hidden_size: []
+actor_hidden_size: [64, 64]
+critic_hidden_size: [64, 64]
 activation: "ReLU"
 
 seed: 1

xuance/configs/mappo/sc2/8m_vs_9m.yaml

@@ -12,16 +12,16 @@ on_policy: True
 use_recurrent: True
 rnn: "GRU"
 recurrent_layer_N: 1
-fc_hidden_sizes: [64, 64, 64]
+fc_hidden_sizes: [64,]
 recurrent_hidden_size: 64
 N_recurrent_layers: 1
 dropout: 0
 normalize: "LayerNorm"
 initialize: "orthogonal"
 gain: 0.01
 
-actor_hidden_size: []
-critic_hidden_size: []
+actor_hidden_size: [64, 64]
+critic_hidden_size: [64, 64]
 activation: "ReLU"
 
 seed: 1

xuance/torch/agents/multi_agent_rl/mappo_agents.py

@@ -40,8 +40,6 @@ def __init__(self,
         optimizer = torch.optim.Adam(policy.parameters(),
                                      lr=config.learning_rate, eps=1e-5,
                                      weight_decay=config.weight_decay)
-        scheduler = torch.optim.lr_scheduler.LinearLR(optimizer, start_factor=1.0, end_factor=0.5,
-                                                      total_iters=config.running_steps)
         self.observation_space = envs.observation_space
         self.action_space = envs.action_space
         self.auxiliary_info_shape = {}
@@ -54,8 +52,7 @@ def __init__(self,
         self.buffer_size = memory.buffer_size
         self.batch_size = self.buffer_size // self.n_minibatch
 
-        learner = MAPPO_Clip_Learner(config, policy, optimizer, scheduler,
-                                     config.device, config.model_dir, config.gamma)
+        learner = MAPPO_Clip_Learner(config, policy, optimizer, None, config.device, config.model_dir, config.gamma)
         super(MAPPO_Agents, self).__init__(config, envs, policy, memory, learner, device,
                                            config.log_dir, config.model_dir)
         self.share_values = True if config.rew_shape[0] == 1 else False