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config.py

+# Simulation parameters
+NUM_EPISODES = 1000
+NUM_EPISODES_DQN = 500
+NUM_EPISODES_SARSA=2000
+MAX_STEPS = 500
+
+# Control algorithm parameters
+'''CONTROL_PARAMS = {
+    'learning_rate': 0.1,
+    'discount_factor': 0.99,
+    'epsilon': 0.1,
+    'patience': 10,          # Number of episodes to wait before reducing learning rate if no improvement
+    'min_delta': 0.01,       # Minimum change in reward to be considered an improvement
+    'decay_factor': 0.9      # Factor by which to multiply the learning rate when performance plateaus
+}'''
+
+CONTROL_PARAMS = {
+    'learning_rate': 0.001,
+    'discount_factor': 0.99,
+    'epsilon': 1.0,
+    'min_epsilon': 0.01,
+    'decay_rate': 0.995,
+    'buffer_size': 10000,  # For DQN
+    'batch_size': 64,      # For DQN
+    'update_target_steps': 1000,  # For DQN
+    'patience': 50,          
+    'min_delta': 0.01,       
+    'decay_factor': 0.9
+}
+
+# Logging parameters
+LOG_PARAMS = {
+    'log_frequency': 10,
+    'save_path': './Results/'
+}
+
+# Hardware interface parameters (when using real hardware)
+HARDWARE_PARAMS = {
+    'motor_pins': [18, 23],  # Example GPIO pins
+    'encoder_pins': [24, 25],
+    'update_frequency': 50  # Hz
+}
+
+EARLY_STOPPING = {
+    'patience': 10,  # Number of episodes with no improvement after which training will be stopped
+    'min_delta': 1e-5  # Minimum change to consider as an improvement
+}
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