private Result Run(Evaluator evaluator, Board board, Player player, int depth, int alpha, int beta)
{
hits++;
if (depth == 0 || board.Winner != Player.None)
{
return(new Result(null, evaluator.Run(board, player)));
}
Result best = new Result(null, -inf);
List <Move> moves = board.GetPossibleMovesSorted(player);
if (depth == start)
{
total = moves.Count;
}
foreach (Move move in moves)
{
Transition transition = board.PerformMove(move);
Result candidate = Run(evaluator, board, BackendHelper.SwapPlayer(player), depth - 1, -beta, -alpha);
board.ReverseTransition(transition);
if (-candidate.Value > best.Value)
{
best = new Result(move, -candidate.Value);
}
if (best.Value >= beta)
{
break;
}
if (best.Value > alpha)
{
alpha = best.Value;
}
if (depth == start)
{
done++;
}
}
return(best);
}
private Result RunInternal(Evaluator evaluator, Board board, Player player, int depth)
{
hits++;
if (depth == 0 || board.Winner != Player.None)
{
return(new Result(null, evaluator.Run(board, player)));
}
Result winner = new Result(null, int.MinValue);
List <Move> moves = board.GetPossibleMovesSorted(player);
if (depth == start)
{
total = moves.Count;
}
foreach (Move move in moves)
{
Transition transition = board.PerformMove(move);
Result candidate = RunInternal(evaluator, board, BackendHelper.SwapPlayer(player), depth - 1);
if (-candidate.Value > winner.Value)
{
winner = new Result(move, -candidate.Value);
}
board.ReverseTransition(transition);
if (depth == start)
{
done++;
}
}
return(winner);
}
private Result Run(Evaluator evaluator, Board board, Player player, int depth, int alpha, int beta)
{
hits++;
if (depth == 0 || board.Winner != Player.None)
{
return(new Result(null, evaluator.Run(board, player)));
}
int prevalpha = alpha;
Transposition transposition = transTable.Lookup(board, player);
if (transposition != null && transposition.Depth >= depth)
{
switch (transposition.Bound)
{
case EvaluationBound.Lower:
alpha = Math.Max(alpha, transposition.BestMove.Value);
break;
case EvaluationBound.Upper:
beta = Math.Min(beta, transposition.BestMove.Value);
break;
case EvaluationBound.Accurate:
alpha = beta = transposition.BestMove.Value;
break;
}
if (alpha >= beta)
{
return(transposition.BestMove);
}
}
List <Move> possibleMoves = board.GetPossibleMovesSorted(player);
if (depth == start)
{
total = possibleMoves.Count;
}
if (transposition != null)
{
int index = possibleMoves.IndexOf(transposition.BestMove.Move);
if (index == -1)
{
throw new Exception(String.Format("Move \"{0}\" not found.", transposition.BestMove.Move));
}
possibleMoves[index] = possibleMoves[0];
possibleMoves[0] = transposition.BestMove.Move;
}
Result best = new Result(null, -inf);
foreach (Move move in possibleMoves)
{
Transition transition = board.PerformMove(move);
Result candidate = Run(evaluator, board, BackendHelper.SwapPlayer(player), depth - 1, -beta, -alpha);
board.ReverseTransition(transition);
if (-candidate.Value > best.Value)
{
best = new Result(move, -candidate.Value);
}
if (best.Value >= beta)
{
break;
}
if (best.Value > alpha)
{
alpha = best.Value;
}
if (depth == start)
{
done++;
}
}
transTable.Save(board, best, prevalpha, beta, depth);
return(best);
}
