public override FutureMove Think(Board board, CancellationToken ct)
{
Winner winner;
PColor colorOfOurAI = board.Turn;
possibleMoves.Clear();
nonLosingMoves.Clear();
for (int col = 0; col < Cols; col++)
{
if (board.IsColumnFull(col))
{
continue;
}
for (int shp = 0; shp < 2; shp++)
{
PShape shape = (PShape)shp;
if (board.PieceCount(colorOfOurAI, shape) == 0)
{
continue;
}
possibleMoves.Add(new FutureMove(col, shape));
board.DoMove(shape, col);
winner = board.CheckWinner();
// immediately
board.UndoMove();
if (winner.ToPColor() == colorOfOurAI)
{
return(new FutureMove(col, shape));
}
else if (winner.ToPColor() != colorOfOurAI.Other())
{
nonLosingMoves.Add(new FutureMove(col, shape));
}
}
}
if (nonLosingMoves.Count > 0)
{
return(nonLosingMoves[random.Next(nonLosingMoves.Count)]);
}
return(possibleMoves[random.Next(possibleMoves.Count)]);
}
// Raise and invalid play event and return the match winner (which is
// the opponent of the thinker that made an invalid play)
private Winner OnInvalidPlay(
PColor color, IThinker thinker, string reason)
{
// Set the other thinker as the winner of the match
Winner winner = color.Other().ToWinner();
// Set solution to null
solution = null;
// Notify listeners that thinker made an invalid play
InvalidPlay?.Invoke(color, thinker.ToString(), reason);
// Return the winner
return(winner);
}
// Negamax with alpha beta pruning.
private (FutureMove move, float score) Negamax(
Board board, CancellationToken ct, PColor turn, int depth,
float alpha, float beta)
{
(FutureMove move, float score)currentMove;
Winner winner;
// In case of cancellation request, skips rest of algorithm.
if (ct.IsCancellationRequested)
{
// Makes no move.
currentMove = (FutureMove.NoMove, float.NaN);
}
// If game has ended, returns final score.
else if ((winner = board.CheckWinner()) != Winner.None)
{
// Oizys wins, returns maximum score.
if (winner.ToPColor() == turn)
{
currentMove = (FutureMove.NoMove, float.PositiveInfinity);
}
// Opponent wins, returns minimum score.
else if (winner.ToPColor() == turn.Other())
{
currentMove = (FutureMove.NoMove, float.NegativeInfinity);
}
// A draw board, return 0.
else
{
currentMove = (FutureMove.NoMove, 0f);
}
}
// If maximum depth has been reached, get heuristic value.
else if (depth == maxDepth)
{
currentMove = (FutureMove.NoMove, Heuristic(board, turn));
}
// Board isn't final and maximum depth hasn't been reached.
else
{
// Set up currentMove for future maximizing.
currentMove = (FutureMove.NoMove, float.NegativeInfinity);
// Iterate each column.
for (int c = 0; c < Cols; c++)
{
// If column is full, skip to next column.
if (board.IsColumnFull(c))
{
continue;
}
// Try both shapes.
for (int s = 0; s < 2; s++)
{
// Store current shape.
PShape shape = (PShape)s;
// If player doesn't have this piece, skip.
if (board.PieceCount(turn, shape) == 0)
{
continue;
}
// Test move.
board.DoMove(shape, c);
// Call Negamax and register board's score.
float score = -Negamax(
board, ct, turn.Other(), depth + 1, -beta,
-alpha).score;
// Undo move.
board.UndoMove();
// If this move has the best score yet, keep it.
if (score > currentMove.score)
{
currentMove = (new FutureMove(c, shape), score);
}
// Update alpha value.
if (score > alpha)
{
alpha = score;
}
// Beta pruning.
if (alpha >= beta)
{
return(currentMove);
}
}
}
}
// Returns move and its value.
return(currentMove);
}
// Our minimax implementation
private (FutureMove move, float score) Minimax(
Board board, CancellationToken ct, PColor player, PColor turn, int depth)
{
// Move to return and its heuristic value
(FutureMove move, float score)selectedMove;
// Current board state
Winner winner;
// If a cancellation request was made...
if (ct.IsCancellationRequested)
{
// ...set a "no move" and skip the remaining part of the algorithm
selectedMove = (FutureMove.NoMove, float.NaN);
}
// Otherwise, if it's a final board, return the appropriate evaluation
else if ((winner = board.CheckWinner()) != Winner.None)
{
if (winner.ToPColor() == player)
{
// AI player wins, return highest possible score
selectedMove = (FutureMove.NoMove, float.PositiveInfinity);
}
else if (winner.ToPColor() == player.Other())
{
// Opponent wins, return lowest possible score
selectedMove = (FutureMove.NoMove, float.NegativeInfinity);
}
else
{
// A draw, return zero
selectedMove = (FutureMove.NoMove, 0f);
}
}
// If we're at maximum depth and don't have a final board, use
// the heuristic
else if (depth == maxDepth)
{
// Where did this Heuristic() function come from?
// We'll return to it in a moment
selectedMove = (FutureMove.NoMove, Heuristic(board, player));
}
else // Board not final and depth not at max...
{
//...so let's test all possible moves and recursively call Minimax()
// for each one of them, maximizing or minimizing depending on who's
// turn it is
// Initialize the selected move...
selectedMove = turn == player
// ...with negative infinity if it's the AI's turn and we're
// maximizing (so anything except defeat will be better than this)
? (FutureMove.NoMove, float.NegativeInfinity)
// ...or with positive infinity if it's the opponent's turn and we're
// minimizing (so anything except victory will be worse than this)
: (FutureMove.NoMove, float.PositiveInfinity);
// Test each column
for (int i = 0; i < Cols; i++)
{
// Skip full columns
if (board.IsColumnFull(i))
{
continue;
}
// Test shapes
for (int j = 0; j < 2; j++)
{
// Get current shape
PShape shape = (PShape)j;
// Use this variable to keep the current board's score
float eval;
// Skip unavailable shapes
if (board.PieceCount(turn, shape) == 0)
{
continue;
}
// Test move, call minimax and undo move
board.DoMove(shape, i);
eval = Minimax(board, ct, player, turn.Other(), depth + 1).score;
board.UndoMove();
// If we're maximizing, is this the best move so far?
if (turn == player && eval > selectedMove.score)
{
// If so, keep it
selectedMove = (new FutureMove(i, shape), eval);
}
// Otherwise, if we're minimizing, is this the worst move so far?
else if (turn == player.Other() && eval < selectedMove.score)
{
// If so, keep it
selectedMove = (new FutureMove(i, shape), eval);
}
}
}
}
// Return selected move and its heuristic value
return(selectedMove);
}
