/// <summary>
/// Recursive alpha beta pruning minimax search strategy.
/// </summary>
/// <param name="gbs">The Game Board State.</param>
/// <param name="searchLevels">The number of levels to search (depth)</param>
/// <param name="currentPlayer">The current player's turn.</param>
/// <param name="BestMove">The best move found during the search</param>
/// <param name="alpha">Starting alpha value.</param>
/// <param name="beta">Starting beta value.</param>
/// <returns></returns>
public static AIMinMaxResult AIMinMaxSearch(this IGameBoardState gbs, int searchLevels, Player.PlayerNumber currentPlayer, bool QuiescenceSearch = false, double alpha = -1.0, double beta = 1.0)
{
Move BestMove = null;
double checkWinner = gbs.CheckWinner();
//cutoff for search (recursive base cases)
if (checkWinner == -1.0)
{
return(new AIMinMaxResult(BestMove, -1.0, 1));
}
if (checkWinner == 1.0)
{
return(new AIMinMaxResult(BestMove, 1.0, 1));
}
if (searchLevels == 0)
{
return(new AIMinMaxResult(BestMove, gbs.CalculateUtility(), 1));
}
AIMinMaxResult result = null;
long statesSearched = 0;
//iterate by looking at all possible moves for each piece
List <IPieceState> pieces = gbs.GetAlivePieces().Where(s => s.GetPlayer() == currentPlayer).Select(s => s).ToList();
foreach (IPieceState piece in pieces.Shuffle())
{
List <Move> moves;
if (QuiescenceSearch)
{
moves = MoveGenerator.GetCaptureMoves(gbs, piece);
}
else
{
moves = MoveGenerator.GetMoves(gbs, piece);
}
MovesSearched += moves.Count;
//perform each move on a cloned board and search clone recursively, swapping players each turn
foreach (Move move in moves.Shuffle())
{
IGameBoardState clone = gbs.Clone();
clone.Move(move.piece, move.space);
if (currentPlayer == Player.PlayerNumber.Player1)
{
result = clone.AIMinMaxSearch(searchLevels - 1, Player.PlayerNumber.Player2, true, alpha, beta);
statesSearched += result.TotalStatesSearched;
if (statesSearched > StatesSearched)
{
StatesSearched = statesSearched;
}
if (result.AlphaBeta > alpha)
{
alpha = result.AlphaBeta;
BestMove = move;
}
//beta cut off
if (beta <= alpha)
{
break;
}
}
else /* (currentPlayer == Player.PlayerNumber.Player2) */
{
result = clone.AIMinMaxSearch(searchLevels - 1, Player.PlayerNumber.Player1, true, alpha, beta);
statesSearched += result.TotalStatesSearched;
if (statesSearched > StatesSearched)
{
StatesSearched = statesSearched;
}
if (result.AlphaBeta < beta)
{
beta = result.AlphaBeta;
BestMove = move;
}
//alpha cut off
if (beta <= alpha)
{
break;
}
}
if (jobStatus == AIMinMaxJobStatus.StopRequested && LevelsSearched > 0)
{
searchLevels = 1;
}
}
if (jobStatus == AIMinMaxJobStatus.StopRequested && LevelsSearched > 0)
{
searchLevels = 1;
}
}
//no moves found, treat as a base case
if (BestMove == null)
{
return(new AIMinMaxResult(BestMove, gbs.CalculateUtility(), 1));
}
//Create a result and return it
return(new AIMinMaxResult(BestMove, result.AlphaBeta, statesSearched));
}
