public void testIterativeDeepeningAlphaBetaDecision()
{
IterativeDeepeningAlphaBetaSearch <TicTacToeState, XYLocation, string>
search = IterativeDeepeningAlphaBetaSearch <TicTacToeState, XYLocation, string>
.createFor(game, 0.0, 1.0, 100);
search.makeDecision(state);
int expandedNodes = search.getMetrics().getInt(MinimaxSearch <TicTacToeState, XYLocation, string> .METRICS_NODES_EXPANDED);
Assert.AreEqual(76035, expandedNodes);
}
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);
}
