This is a repository containing all codes/reports/images of the three-phase FinalProject in Artifical Intelligence(DATA130008.01). All the agents in this project are submitted and evaluated via Kaggle.

• Adapted from the Connect X competition in Kaggle.
• You need to implement a MCTS(Monte Carlo Tree Search) agent for the game.

• You need to choose one game from Connect X, Santa, Kore and Lux AI to implement a RL(Reinforcement Learning) agent.
• The RL should be based on value/policy iteration in this phase.

• You need to make a poster and give a presentation in no more than 2 minutes to clarify your agent implemented in FinalProject2.
• The method is not confined to value/policy iteration any more. Any method is allowed in this phase.
• Requirements can be found here.

We choose Santa in phase 2. The best agents of our team in Connect X and Santa all rank second in the leaderboard. Below are the tables display the Kaggle scores of our submissions.