SamiSani68
commented
10 months ago Dear Salvatore,
Thank you for your encouraging feedback on my Tic-Tac-Toe project. I'm glad the code's structure and the QLearningAgent's implementation came across clearly. Your appreciation for the use of defaultdict and the adjustable Q-learning parameters is much appreciated. It's great to hear that the code is user-friendly and approachable.
Thanks again for your kind words and helpful insights!
Best, Samaneh
This code implements a tic-tac-toe (Tic-Tac-Toe) game in which two agents play against each other. One of the agents follows a machine learning approach called Q-learning to improve its moves over time. The QLearningAgent class implements an agent that learns using the Q-learning algorithm. The agent tries to maximize its score by choosing actions that lead to a more advantageous state. The State class is a good choice to represent the state of the game. Using objects makes your code more object-oriented and organized. Using defaultdict to handle Q values of states reduces code complexity. It eliminates the need to check for a key before updating it. One really important thing is that Q-learning agent parameters such as epsilon, alpha and gamma are configurable, allowing for greater flexibility in experiment and parameter optimization . Finally we can say that the code is clear, readable and uses good programming practices that make it easy to use even for an external user who sees it for the first time