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AIMA-Java Core Algorithms from the book Artificial Intelligence a Modern Approach 3rd Ed.
package aima.core.environment.tictactoe;
import java.util.List;
import aima.core.search.adversarial.Game;
import aima.core.util.datastructure.XYLocation;
/**
* Provides an implementation of the Tic-tac-toe game which can be used for
* experiments with the Minimax algorithm.
*
* @author Ruediger Lunde
*
*/
public class TicTacToeGame implements Game {
TicTacToeState initialState = new TicTacToeState();
@Override
public TicTacToeState getInitialState() {
return initialState;
}
@Override
public String[] getPlayers() {
return new String[] { TicTacToeState.X, TicTacToeState.O };
}
@Override
public String getPlayer(TicTacToeState state) {
return state.getPlayerToMove();
}
@Override
public List getActions(TicTacToeState state) {
return state.getUnMarkedPositions();
}
@Override
public TicTacToeState getResult(TicTacToeState state, XYLocation action) {
TicTacToeState result = state.clone();
result.mark(action);
return result;
}
@Override
public boolean isTerminal(TicTacToeState state) {
return state.getUtility() != -1;
}
@Override
public double getUtility(TicTacToeState state, String player) {
double result = state.getUtility();
if (result != -1) {
if (player == TicTacToeState.O)
result = 1 - result;
} else {
throw new IllegalArgumentException("State is not terminal.");
}
return result;
}
}
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