Update README.md

README.md

@@ -32,4 +32,29 @@ model-index:
   # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
   env = gym.make(model["env_id"])
   ```
-  
+
+  To make this Q-learning agent work requires more extended training; otherwise the agent never successfully reaches the end goal and convergence does not take place.
+
+  In my case I found 50 million training steps sufficient with the following hyperparameters:
+
+```python
+# Training parameters
+n_training_episodes = 50000000  # Total training episodes
+learning_rate = 0.99           # Learning rate
+
+# Evaluation parameters
+n_eval_episodes = 100        # Total number of test episodes
+
+# Environment parameters
+env_id = "FrozenLake-v1"     # Name of the environment
+max_steps = 200             # Max steps per episode
+gamma = 0.99                 # Discounting rate
+epsilon = 0.1                # Ideal Episolon
+eval_seed = []               # The evaluation seed of the environment
+
+# Exploration parameters
+max_epsilon = 1             # Exploration probability at start
+min_epsilon = 0.05            # Minimum exploration probability
+decay_rate = 0.0005            # Exponential decay rate for exploration prob
+
+```