public void testMinmaxValueCalculation()
{
MinimaxSearch <TicTacToeState, XYLocation, string> search = MinimaxSearch <TicTacToeState, XYLocation, string> .createFor(game);
Assert.IsTrue(epsilon > System.Math.Abs(search.maxValue(state, TicTacToeState.X) - 0.5));
Assert.IsTrue(epsilon > System.Math.Abs(search.minValue(state, TicTacToeState.O) - 0.5));
// x o x
// o o x
// - - -
// next move: x
state.mark(0, 0); // x
state.mark(1, 0); // o
state.mark(2, 0); // x
state.mark(0, 1); // o
state.mark(2, 1); // x
state.mark(1, 1); // o
Assert.IsTrue(epsilon > System.Math.Abs(search.maxValue(state, TicTacToeState.X) - 1));
Assert.IsTrue(epsilon > System.Math.Abs(search.minValue(state, TicTacToeState.O)));
XYLocation action = search.makeDecision(state);
Assert.AreEqual(new XYLocation(2, 2), action);
}
public void testMinmaxDecision()
{
MinimaxSearch <TicTacToeState, XYLocation, string> search = MinimaxSearch <TicTacToeState, XYLocation, string> .createFor(game);
search.makeDecision(state);
int expandedNodes = search.getMetrics().getInt(MinimaxSearch <TicTacToeState, XYLocation, string> .METRICS_NODES_EXPANDED);
Assert.AreEqual(549945, expandedNodes);
}
static void startMinimaxDemo()
{
System.Console.WriteLine("MINI MAX DEMO\n");
TicTacToeGame game = new TicTacToeGame();
TicTacToeState currState = game.GetInitialState();
IAdversarialSearch <TicTacToeState, XYLocation>
search = MinimaxSearch <TicTacToeState, XYLocation, string> .createFor(game);
while (!(game.IsTerminal(currState)))
{
System.Console.WriteLine(game.GetPlayer(currState) + " playing ... ");
XYLocation action = search.makeDecision(currState);
currState = game.GetResult(currState, action);
System.Console.WriteLine(currState);
}
System.Console.WriteLine("MINI MAX DEMO done");
}
private void Start()
{
Nim game = new Nim(Matches);
MinimaxSearch <NimState, int, int> minimaxSearch = MinimaxSearch <NimState, int, int> .createFor(game);
AlphaBetaSearch <NimState, int, int> alphabetaSearch = AlphaBetaSearch <NimState, int, int> .createFor(game);
NimState state = game.getInitialState();
int action1 = -1;
int action2 = -1;
action1 = minimaxSearch.makeDecision(state);
action2 = alphabetaSearch.makeDecision(state);
Debug.Log("Chosen action is " + action1 + " and node minimax " + minimaxSearch.getMetrics());
Debug.Log("Chosen action is " + action2 + " and node alphabeta " + alphabetaSearch.getMetrics());
}
private void Start()
{
TTT game = new TTT();
MinimaxSearch <StateTTT, int, int> minimaxSearch = MinimaxSearch <StateTTT, int, int> .createFor(game);
AlphaBetaSearch <StateTTT, int, int> alphabetaSearch = AlphaBetaSearch <StateTTT, int, int> .createFor(game);
StateTTT state = game.getInitialState();
int action1 = -100000;
int action2 = -100000;
action1 = minimaxSearch.makeDecision(state);
action2 = alphabetaSearch.makeDecision(state);
Debug.Log("Chosen action is " + action1 + " and node minimax " + minimaxSearch.getMetrics());
Debug.Log("Chosen action is " + action2 + " and node alphabeta " + alphabetaSearch.getMetrics());
}
public List <GameMoveResult> MakeMoves(Game objGame, object state, int movesNumber)
{
var toReturn = new List <GameMoveResult>();
AdversarialSearch objGameStrategy;
switch (StrategyType)
{
case GameStrategyType.AlphaBeta:
objGameStrategy = AlphaBetaSearch.createFor(objGame);
break;
case GameStrategyType.IterativeDeepeningAlphaBeta:
objGameStrategy = IterativeDeepeningAlphaBetaSearch.createFor(objGame, MinUtility, MaxUtility, MaxDurationSeconds);
break;
case GameStrategyType.ConnectFourIDAlphaBeta:
objGameStrategy = new ConnectFourAIPlayer(objGame, MaxDurationSeconds);
break;
default:
objGameStrategy = MinimaxSearch.createFor(objGame);
break;
}
int counter = 0;
while (!objGame.isTerminal(state) && counter < movesNumber)
{
var action = objGameStrategy.makeDecision(state);
var newMove = new GameMoveResult()
{
Game = objGame, InitialState = state, Action = action, Metrics = objGameStrategy.getMetrics()
};
toReturn.Add(newMove);
state = newMove.ResultState;
counter++;
}
return(toReturn);
}