Description: Developed and implemented a sophisticated AI "CleverBrain" for the classic game of Tetris using Java. The project involved leveraging object-oriented programming concepts and the existing Tetris framework provided, including classes such as Brain, Point, Piece, Board, Move, and JTetris.

Key Achievements:

AI Brain Development: Designed and coded an AI "CleverBrain" that acts as an automated Tetris player. The AI brain was programmed to evaluate Tetris board states and make optimal decisions for piece placements based on a variety of factors.

Brain Interface Implementation: Successfully implemented the Brain interface, which required the creation of methods to rate the game board's current state and select the best move for each incoming Tetris piece.

Algorithm Design: Employed a stepwise refinement approach to create a robust rateBoard() method, focusing on factors such as column heights, hole counts, and piece placements. The algorithm considered the height limit and aimed to maximize board efficiency.

Brute Force Optimization: Developed the bestMove() method to explore all possible piece rotations and positions for each incoming piece, selecting the move with the lowest-rated board state as the optimal choice.

Testing and Refinement: Conducted thorough testing of the AI brain to ensure its effectiveness in playing Tetris. Refinement of the rateBoard() algorithm and bestMove() logic was performed iteratively to improve gameplay.

Outcome: The Tetris AI Brain, "CleverBrain," demonstrated the ability to consistently make intelligent decisions in real-time Tetris gameplay. The project showcases expertise in artificial intelligence and algorithm design, highlighting a practical application of AI concepts in the context of a classic video game.