Use bigger neural network

src/experiments/game_theory_blocking/run_blocking_model.py

@@ -139,5 +139,6 @@ if __name__ == "__main__":
 
     log_file = f'{base_dir}/log'
     with open(log_file, 'a') as log:
+        sys.stderr = log
         sys.stdout = log
         main(experiment_conf, base_dir)

src/experiments/game_theory_latency/run_latency_model.py

@@ -139,6 +139,7 @@ if __name__ == "__main__":
 
     log_file = f'{base_dir}/log'
     with open(log_file, 'a') as log:
+        sys.stderr = log
         sys.stdout = log
         main(experiment_conf, base_dir)
 

src/experiments/learning_epochs/configuration.yaml

 experiments_per_setup: 8  # 6
-legacy_folder: /home/ignac/experiments/learning_epochs/18000to30000by4000_8times # Change in regards with configuration
+legacy_folder: /home/ignac/experiments/learning_epochs/2000to30000by4000_8times # Change in regards with configuration
 epochs:
-  lower_bound: 18000
-  number_of_steps: 4  # 8 (6-8 should be enough)
+  lower_bound: 2000
+  number_of_steps: 8  # 8 (6-8 should be enough)
   upper_bound: 30000  # 30000
 conf:
   i_a: 1

src/experiments/learning_epochs/learning_epochs.py

@@ -177,6 +177,7 @@ if __name__ == "__main__":
 
     log_file = f'{base_dir}/log'
     with open(log_file, 'a') as log:
+        sys.stderr = log
         sys.stdout = log
         main(experiment_conf, base_dir)
     # main(experiment_conf, base_dir)

src/neural_networks/network.py

@@ -70,13 +70,13 @@ class NeuralNetwork:
     def __init__(self, input_features=2,
                  nn_conf: NeuralNetworkConfig = NeuralNetworkConfig()):
         self.model = nn.Sequential(
-            nn.Linear(input_features, 5),
+            nn.Linear(input_features, 20),
             nn.ReLU(),
-            nn.Linear(5, 5),
+            nn.Linear(20, 15),
             nn.ReLU(),
-            nn.Linear(5, 5),
+            nn.Linear(15, 20),
             nn.ReLU(),
-            nn.Linear(5, 1),
+            nn.Linear(20, 1),
             nn.Tanh(),
             SoftClip(50)
             # nn.Sigmoid()