public static int[] CalculateOptimalAssignment(List <Task> newGoals, List <CreatureAI> agents)
{
int numGoals = newGoals.Count;
int numAgents = agents.Count;
int maxSize = Math.Max(numGoals, numAgents);
int[,] goalMatrix = new int[maxSize, maxSize];
const float multiplier = 100;
if (numGoals == 0 || numAgents == 0)
{
return(null);
}
for (int goalIndex = 0; goalIndex < numGoals; goalIndex++)
{
Task goal = newGoals[goalIndex];
for (int agentIndex = 0; agentIndex < numAgents; agentIndex++)
{
CreatureAI agent = agents[agentIndex];
float floatCost = goal.ComputeCost(agent.Creature);
int cost = (int)(floatCost * multiplier);
if (!goal.IsFeasible(agent.Creature))
{
cost += 99999;
}
if (agent.Creature.Status.IsAsleep)
{
cost += 99999;
}
cost += agents[agentIndex].Tasks.Count;
goalMatrix[agentIndex, goalIndex] = cost;
}
}
// Add additional columns or rows
if (numAgents > numGoals)
{
int maxValue = GetMax(goalMatrix, numAgents, numGoals) + 1;
for (int dummyGoal = numGoals; dummyGoal < maxSize; dummyGoal++)
{
for (int i = 0; i < numAgents; i++)
{
// If we have more agents than goals, we need to add additional fake goals
// Since goals are in columns, we are essentially adding a new column.
goalMatrix[i, dummyGoal] = maxValue;
}
}
}
else if (numGoals > numAgents)
{
int maxValue = GetMax(goalMatrix, numAgents, numGoals) + 1;
for (int dummyAngent = numAgents; dummyAngent < maxSize; dummyAngent++)
{
for (int i = 0; i < numGoals; i++)
{
// If we have more goals than agents, we need to add additional fake agents
// Since goals are in columns, we are essentially adding a new row.
goalMatrix[dummyAngent, i] = maxValue;
}
}
}
return(goalMatrix.FindAssignments());
}
public static void AssignTasksGreedy(List <Task> newGoals, List <CreatureAI> creatures, int maxPerGoal)
{
string trackingString = "AssignTasksGreedy(" + newGoals.Count + ")";
GamePerformance.Instance.StartTrackPerformance(trackingString);
// We are going to keep track of the unassigned goal count
// to avoid having to parse the list at the end of the loop.
int goalsUnassigned = newGoals.Count;
List <int> counts = new List <int>(goalsUnassigned);
for (int i = 0; i < goalsUnassigned; i++)
{
counts.Add(0);
}
// Randomized list changed from the CreatureAI objects themselves to an index into the
// List passed in. This is to avoid having to shift the masterCosts list around to match
// each time we randomize.
List <int> randomIndex = new List <int>(creatures.Count);
for (int i = 0; i < creatures.Count; i++)
{
randomIndex.Add(i);
}
// We create the comparer outside of the loop. It gets reused for each sort.
CostComparer toCompare = new CostComparer();
// One of the biggest issues with the old function was that it was recalculating the whole task list for
// the creature each time through the loop, using one item and then throwing it away. Nothing changed
// in how the calculation happened between each time so we will instead make a costs list for each creature
// and keep them all. This not only avoids rebuilding the list but the sheer KeyValuePair object churn there already was.
List <List <KeyValuePair <int, float> > > masterCosts = new List <List <KeyValuePair <int, float> > >(creatures.Count);
// We will set this up in the next loop rather than make it's own loop.
List <int> costsPositions = new List <int>(creatures.Count);
for (int costIndex = 0; costIndex < creatures.Count; costIndex++)
{
List <KeyValuePair <int, float> > costs = new List <KeyValuePair <int, float> >();
CreatureAI creature = creatures[costIndex];
// We already were doing an index count to be able to make the KeyValuePair for costs
// and foreach uses Enumeration which is slower.
for (int i = 0; i < newGoals.Count; i++)
{
Task task = newGoals[i];
// We are checking for tasks the creature is already assigned up here to avoid having to check
// every task in the newGoals list against every task in the newGoals list. The newGoals list
// should reasonably not contain any task duplicates.
if (creature.Tasks.Contains(task))
{
continue;
}
float cost = 0;
// We've swapped the order of the two checks to take advantage of a new ComputeCost that can act different
// if we say we've already called IsFeasible first. This allows us to skip any calculations that are repeated in both.
if (!task.IsFeasible(creature.Creature))
{
cost += 1e10f;
}
cost += task.ComputeCost(creature.Creature, true);
costs.Add(new KeyValuePair <int, float>(i, cost));
}
// The sort lambda function has been replaced by an IComparer class.
// This is faster but I mainly did it because VS can not Edit & Continue
// any function with a Lambda function in it which was slowing down dev time.
costs.Sort(toCompare);
masterCosts.Add(costs);
costsPositions.Add(0);
}
// We are going to precalculate the maximum iterations and count down
// instead of up.
int iters = goalsUnassigned * creatures.Count;
while (goalsUnassigned > 0 && iters > 0)
{
randomIndex.Shuffle();
iters--;
for (int creatureIndex = 0; creatureIndex < randomIndex.Count; creatureIndex++)
{
int randomCreature = randomIndex[creatureIndex];
CreatureAI creature = creatures[randomCreature];
List <KeyValuePair <int, float> > costs = masterCosts[randomCreature];
int costPosition = costsPositions[randomCreature];
// This loop starts with the previous spot we stopped. This avoids us having to constantly run a task we
// know we have processed.
for (int i = costPosition; i < costs.Count; i++)
{
// Incremented at the start in case we find a task and break.
costPosition++;
KeyValuePair <int, float> taskCost = costs[i];
// We've swapped the checks here. Tasks.Contains is far more expensive so being able to skip
// if it's going to fail the maxPerGoal check anyways is very good.
if (counts[taskCost.Key] < maxPerGoal)// && !creature.Tasks.Contains(newGoals[taskCost.Key]))
{
// We have to check to see if the task we are assigning is fully unassigned. If so
// we reduce the goalsUnassigned count. If it's already assigned we skip it.
if (counts[taskCost.Key] == 0)
{
goalsUnassigned--;
}
counts[taskCost.Key]++;
creature.Tasks.Add(newGoals[taskCost.Key].Clone());
break;
}
}
// We have to set the position we'll start the loop at the next time based on where we found
// our task.
costsPositions[randomCreature] = costPosition;
// The loop at the end to see if all are unassigned is gone now, replaced by a countdown
// variable: goalsUnassigned.
}
}
GamePerformance.Instance.EndTrackPerformance(trackingString);
}