public int BlockCount()
{
Cell.CellOcc oppType = SignResourceStorage.GetOppositeOfSign(type);
bool block1 = blockField1.type == oppType || blockField1.type == Cell.CellOcc.BLOCKED;
bool block2 = blockField2.type == oppType || blockField2.type == Cell.CellOcc.BLOCKED;
if (block1 && block2)
{
return(2);
}
else if (block1 || block2)
{
return(1);
}
else
{
return(0);
}
}
/// <summary>
/// A recursive minimax algorithm with alpha beta pruning
/// </summary>
private EvaluationResult EvaluateField(EvaluationField[,] field, Cell.CellOcc whoseTurn, int deepCount, List <IntVector2> pointsInGame, float alpha, float beta)
{
EvaluationResult result = new EvaluationResult(whoseTurn == HumanType ? int.MaxValue : int.MinValue, new IntVector2());
List <IntVector2> been = new List <IntVector2>();
int pointsInGameLength = pointsInGame.Count;
bool alphaBetaEnd = false;
// Go through the places where we can place
// Call NewSignPlaced with field and position where we want to place
for (int j = pointsInGame.Count - 1; j >= 0; j--)
{
// In each direction
for (int i = -1; i <= 1 && !alphaBetaEnd; i++)
{
for (int k = -1; k <= 1 && !alphaBetaEnd; k++)
{
// we just skip a place if we feel like, just to make AI a bit easier
if (rand.NextDouble() <= leaveOutChance + pointsInGame.Count / (float)afterSignCountMiss)
{
continue;
}
IntVector2 pos = new IntVector2(pointsInGame[j].x + i, pointsInGame[j].y + k);
// Not 0 0 and in bounds
if (!(i == 0 && k == 0) && /*&& pos.x >= 0 && pos.x < field.GetLength(0) && pos.y >= 0 && pos.y < field.GetLength(1)*/
field[pos.x, pos.y].type == Cell.CellOcc.NONE && !been.Contains(pos)) // if we haven't checked this position and the type of cell we are examining is NONE, so empty
{
been.Add(pos);
// Data so we can revert the field back (because recursive algorithm)
List <PlaceData> placed;
List <PlaceData> removed;
// Set the examined cell to the current's sign
field[pos.x, pos.y].type = whoseTurn;
// Place that sign and while that's happening determine signsinarow
NewSignPlaced(field, pos, out placed, out removed);
pointsInGame.Add(new IntVector2(pos));
// Go recursively until DIFFICULTY
EvaluationResult evalResult;
if (deepCount == DEEP_MAX)
{
float aiPoint, humanPoint;
GetPointsFromSignsInARow(field, pointsInGame, pos, out aiPoint, out humanPoint);
if (whoseTurn == AIType)
{
evalResult.points = aiPoint + humanPoint * 1.5f;
}
else
{
evalResult.points = aiPoint * 1.5f + humanPoint;
}
evalResult.fieldPos = new IntVector2(pos);
}
else
{
evalResult = EvaluateField(field, SignResourceStorage.GetOppositeOfSign(whoseTurn), deepCount + 1, pointsInGame, alpha, beta);
}
// If it is human's turn we search for min value - MINIMIZER
if (whoseTurn == HumanType)
{
if (result.points > evalResult.points)
{
result.points = evalResult.points;
result.fieldPos = new IntVector2(pos);
}
beta = Mathf.Min(beta, result.points);
// If the points here is smaller than the best value for the parent maximizer then we don't have to search further because this minimizer
// potentially has the chance of picking this minimum value, which the parent maximizer will never pick otherwise if this minimizer
// doesn't pick this vaue it's only gonna pick a smaller one which is even worse for the maximizer
// so just stop the search
if (result.points <= alpha)
{
alphaBetaEnd = true;
}
}
// Otherwise if it is AI's turn we search for the max points - MAXIMIZER
else if (whoseTurn == AIType)
{
if (result.points < evalResult.points)
{
result.points = evalResult.points;
result.fieldPos = new IntVector2(pos);
}
alpha = Mathf.Max(alpha, result.points);
// if the point is higher then the minimizer minimum then we don't need to search further because this maximizer
// will surely pick a greater value for the parent minimizer, than it already has
if (result.points >= beta)
{
alphaBetaEnd = true;
}
}
// Revert the field back
for (int l = 0; l < placed.Count; l++)
{
field[placed[l].fieldPos.x, placed[l].fieldPos.y].signsInARow.Remove(placed[l].signInARow);
}
for (int l = 0; l < removed.Count; l++)
{
field[removed[l].fieldPos.x, removed[l].fieldPos.y].signsInARow.Add(removed[l].signInARow);
}
field[pos.x, pos.y].type = Cell.CellOcc.NONE;
pointsInGame.RemoveAt(pointsInGame.Count - 1);
}
}
}
}
return(result);
}
public override void NextTurn(int[] gridPos, out Cell.CellOcc won)
{
Cell.CellOcc didWin;
base.NextTurn(gridPos, out didWin);
// Send to client that sign has been placed
PlayGamesPlatform.Instance.RealTime.SendMessageToAll(true, Encoding.Unicode.GetBytes(
GPMessageStrings.SIGN_PLACED + "#" + gridPos[0].ToString() + "#" + gridPos[1].ToString() + "#" + SignResourceStorage.GetOppositeOfSign(whoseTurn).ToString()
));
// also send whose turn it is
PlayGamesPlatform.Instance.RealTime.SendMessageToAll(true, Encoding.Unicode.GetBytes(
GPMessageStrings.TURN_OF + "#" + whoseTurn.ToString()
));
if (didWin == Cell.CellOcc.X || didWin == Cell.CellOcc.O)
{
if (didWin == Cell.CellOcc.X)
{
xScore++;
}
else
{
oScore++;
}
scoring.SetScore(xScore, oScore);
// send score to client
PlayGamesPlatform.Instance.RealTime.SendMessageToAll(true, Encoding.Unicode.GetBytes(
GPMessageStrings.SEND_SCORE + "#" + xScore.ToString() + "#" + oScore.ToString()
));
}
won = didWin;
}