private void RunNegaMaxAtAParticularDepth()
{
SearchNode newRootNode = new SearchNode(Coordinator.CurrentGameState);
GameState mutableGameState = null;
if (gameStateGenerationMethod == NegaMaxGameStateGenerationMethod.MutableGameStateWithUndo)
{
mutableGameState = Coordinator.CurrentGameState.Clone();
}
double evaluation = Negamax(newRootNode, mutableGameState);
if (SolverState == SolverState.Stopping)
{
newRootNode.EvaluationStatus = EvaluationStatus.Stopped;
}
else
{
RootNode = newRootNode;
LastDepthCompleted = CurrentDepth;
// A solution was found at this depth. Choose a best solution:
RootNode.Evaluation = evaluation;
// Always choose the first child node matching the best evaluation, as other nodes might be a result of pruning:
SearchNode chosenChildNode = RootNode.ChildNodes.Where(
childNode => childNode.EvaluationStatus == EvaluationStatus.Evaluated && childNode.Evaluation == evaluation
).FirstOrDefault();
if (chosenChildNode != null)
{
GameState chosenGameState = chosenChildNode.GameState;
#if DEBUG
// Perform algorithms on chosen node, since search nodes no longer do this (except at leaf nodes):
Dijkstra.Perform(chosenGameState);
BiconnectedComponentsAlgorithm bcAlg = new BiconnectedComponentsAlgorithm();
bcAlg.Calculate(chosenGameState, ReachableCellsThenClosestCellsThenDegreesOfClosestCellsEvaluator.Instance);
#endif
Coordinator.SetBestMoveSoFar(chosenGameState);
}
else
{
Debug.WriteLine("NegaMax found no best child");
}
#if DEBUG
int numberOfEvaluationsAtThisDepth = numberOfEvaluationsByDepth.ContainsKey(CurrentDepth) ? numberOfEvaluationsByDepth[CurrentDepth] : 0;
System.Diagnostics.Debug.WriteLine("*** NegaMax performed {0} evaluations at depth {1}", numberOfEvaluationsAtThisDepth, CurrentDepth);
#endif
}
}
private double Negamax(SearchNode searchNode, GameState gameState, int depth = 0, double alpha = double.NegativeInfinity,
double beta = double.PositiveInfinity)
{
if (gameStateGenerationMethod == NegaMaxGameStateGenerationMethod.GameStatePerSearchNode)
{
gameState = searchNode.GameState;
}
int multiplier;
if (searchNode.ParentNode == null)
{
multiplier = gameState.PlayerToMoveNext == PlayerType.You ? 1 : -1;
}
else
{
// A more efficient way, since it doesn't cause game states to be re-generated:
multiplier = searchNode.Move.PlayerType == PlayerType.Opponent ? 1 : -1;
}
if (depth >= CurrentDepth)
{
// Perform the algorithms on the game state, before running the evaluation:
Dijkstra.Perform(gameState);
BiconnectedComponentsAlgorithm bcAlg = new BiconnectedComponentsAlgorithm();
bcAlg.Calculate(gameState, ReachableCellsThenClosestCellsThenDegreesOfClosestCellsEvaluator.Instance);
Evaluate(searchNode, gameState);
int evaluationsAtThisDepth = numberOfEvaluationsByDepth.ContainsKey(depth) ? numberOfEvaluationsByDepth[depth] : 0;
numberOfEvaluationsByDepth[depth] = evaluationsAtThisDepth + 1;
return(multiplier * searchNode.Evaluation);
}
else
{
searchNode.Expand(gameState);
if (SolverState == SolverState.Stopping)
{
return(0.0); // Calling code will check solver state and ignore the result
}
if (!searchNode.ChildNodes.Any())
{
/* Game is terminal: */
if (gameState.IsGameOver)
{
if (gameState.PlayerToMoveNext == PlayerType.You)
{
searchNode.Evaluation = double.NegativeInfinity;
}
else
{
searchNode.Evaluation = double.PositiveInfinity;
}
}
else
{
throw new ApplicationException("Game state should be over if there are no child search nodes!");
}
return(multiplier * searchNode.Evaluation);
}
else
{
double max = double.NegativeInfinity;
bool pruning = false;
foreach (SearchNode childNode in searchNode.ChildNodes)
{
if (SolverState == SolverState.Stopping)
{
childNode.EvaluationStatus = EvaluationStatus.Stopped;
}
else
if (pruning)
{
childNode.EvaluationStatus = EvaluationStatus.Pruned;
}
else
{
if (gameStateGenerationMethod == NegaMaxGameStateGenerationMethod.MutableGameStateWithUndo)
{
gameState.MakeMove(childNode.Move, false, false); // Don't perform algorithms
}
try
{
double evaluation = -Negamax(childNode, gameState, depth + 1, -beta, -alpha);
if (SolverState == SolverState.Stopping)
{
childNode.EvaluationStatus = EvaluationStatus.Stopped;
return(0.0);
}
else
{
childNode.Evaluation = evaluation;
// Alpha-beta pruning:
if (evaluation > max)
{
max = evaluation;
}
if (evaluation > alpha)
{
alpha = evaluation;
}
if (alpha >= beta)
{
pruning = true;
}
}
}
finally
{
if (gameStateGenerationMethod == NegaMaxGameStateGenerationMethod.MutableGameStateWithUndo)
{
gameState.UndoLastMove();
}
}
}
}
if (pruning)
{
searchNode.EvaluationStatus = EvaluationStatus.Pruned;
return(alpha);
}
return(max);
}
}
}
