AI Tetris using Particle Swarm Optimization
Running application using trained weights
- Maximum height of board
- Average height of board
- Rows cleared by piece
- Number of holes
- Number of column transitions
- Number of row transitions
- Sum of wells in board
- Absolute different of heights in board
This is a basic Tetris simulation.
Files: State - tetris simulation TFrame - frame that draws the board TLabel - drawing library PlayerSkeleton - setup for implementing a player
State: This is the tetris simulation. It keeps track of the state and allows you to make moves. The board state is stored in field (a double array of integers) and is accessed by getField(). Zeros denote an empty square. Other values denote the turn on which that square was placed. NextPiece (accessed by getNextPiece) contains the ID (0-6) of the piece you are about to play.
Moves are defined by two numbers: the SLOT, the leftmost column of the piece and the ORIENT, the orientation of the piece. Legalmoves gives an nx2 int array containing the n legal moves. A move can be made by specifying the two parameters as either 2 ints, an int array of length 2, or a single int specifying the row in the legalMoves array corresponding to the appropriate move.
It also keeps track of the number of lines cleared - accessed by getRowsCleared().
draw() draws the board. drawNext() draws the next piece above the board clearNext() clears the drawing of the next piece so it can be drawn in a different slot/orientation
TFrame: This extends JFrame and is instantiated to draw a state. It can save the current drawing to a .png file. The main function allows you to play a game manually using the arrow keys.
TLabel: This is a drawing library.
PlayerSkeleton: An example of how to implement a player. The main function plays a game automatically (with visualization).