/// <summary>
/// Search the game tree multiple times with increasing depth until the wall clock time limit
/// specified by the configuration is exhausted. Take best result found at that point and
/// cancel search.
/// </summary>
private static Result BestFixedTime(Configuration c, FastWorld w, int ownIndex)
{
Debug.Assert(c.SearchLimit.LimitType == DeepeningSearch.LimitType.Milliseconds);
// Keep in mind on thread safety:
// The thread that calls Abort might block if the thread that is being aborted is in a protected
// region of code, such as a catch block, finally block, or constrained execution region. If the
// thread that calls Abort holds a lock that the aborted thread requires, a deadlock can occur.
// https://docs.microsoft.com/en-us/dotnet/api/system.threading.thread.abort?view=netframework-4.7.2
var myLock = new object();
Result best = null;
var stop = new DeepeningSearch.Stop();
Thread t = new Thread(() => {
try {
for (int i = 1; ; ++i)
{
var result = SearchSelectingStrategy(c, w, ownIndex, i, stop);
lock (myLock) {
best = result;
}
}
}
catch (DeepeningSearch.StopSearchException) {
// Perfectly normal to throw this exception upon stopping deepening
return;
}
});
t.Start();
Thread.Sleep(c.SearchLimit.Limit);
stop.RequestStop();
// Should be no more contention since t is aborted and joined
// But I guess it doesn't hurt
lock (myLock) {
return(best);
}
}
private static Result SearchSelectingStrategy(Configuration c, FastWorld w, int ownIndex, int depth, DeepeningSearch.Stop stop)
{
var reflexMask = c.ReflexMask ?? FindMaskForDepth(w, ownIndex, depth);
var simulatedCount = reflexMask.Count(el => el == false);
var ordering = MaxN.CalculateSteppingOrdering(w, ownIndex, reflexMask);
if (simulatedCount == 2 && c.AlphaBetaFallbackHeuristic != null)
{
// If alpha beta fallback heuristic is provided and we have two simulated snakes, use alpha beta search
var abConf = new DeepeningSearch.Configuration(c.AlphaBetaFallbackHeuristic(ordering[0], ordering[1]), ordering[0], ordering[1]);
abConf.Stop = stop;
var(direction, score) = new AlphaBeta().Search(abConf, w, depth);
return(new Result(new DeepeningSearch.Result(score, direction, depth)));
}
else
{
var internalConfiguration = new InternalConfiguration {
ReflexMask = reflexMask,
Depth = depth,
OwnIndex = ownIndex,
StopHandler = stop
};
var(scoresAbs, scoresRel, directions) = PseudoPlyStep(w, internalConfiguration, c.MaxNHeuristicProducer(ownIndex), 0, 0, ordering, null);
return(new Result(
internalConfiguration.steps,
internalConfiguration.ReflexMask.Count(el => el == false),
internalConfiguration.Depth,
directions[ownIndex],
scoresRel[ownIndex],
scoresAbs,
scoresRel,
directions
));
}
}