Files
OpenRA/OpenRA.Mods.Common/Pathfinder/PathSearch.cs
RoosterDragon 04912ea996 Expose a setting for Weighted A*
Replace Constants.CellCost and Constants.DiagonalCellCost with a dynamically calculated value based on the lowest cost terrain to traverse. Using a fixed value meant the pathfinder heuristics would be incorrect.

In the four default mods, the minimum cost is in fact 100, not 125. This increase would essentially allow the pathfinder to return suboptimal paths up to 25% longer in the worst case, but it would be quicker to do so.

This is exactly what Weighted A* does - overestimate the heuristic by some factor in order to speed up the search by checking fewer routes. This makes the heuristic inadmissible and it may now return suboptimal paths, but their worst case length is bounded by the weight. A weight of 125% will never produce paths more than 25% longer than the shortest, optimal, path.

We set the default weight to 25% to effectively maintain the existing, suboptimal, behaviour due to the choice of the old constant - in future it may prove a useful tuning knob for performance.
2019-11-15 13:05:41 +01:00

158 lines
5.6 KiB
C#

#region Copyright & License Information
/*
* Copyright 2007-2019 The OpenRA Developers (see AUTHORS)
* This file is part of OpenRA, which is free software. It is made
* available to you under the terms of the GNU General Public License
* as published by the Free Software Foundation, either version 3 of
* the License, or (at your option) any later version. For more
* information, see COPYING.
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.CompilerServices;
using OpenRA.Mods.Common.Traits;
using OpenRA.Primitives;
using OpenRA.Traits;
namespace OpenRA.Mods.Common.Pathfinder
{
public sealed class PathSearch : BasePathSearch
{
// PERF: Maintain a pool of layers used for paths searches for each world. These searches are performed often
// so we wish to avoid the high cost of initializing a new search space every time by reusing the old ones.
static readonly ConditionalWeakTable<World, CellInfoLayerPool> LayerPoolTable = new ConditionalWeakTable<World, CellInfoLayerPool>();
static readonly ConditionalWeakTable<World, CellInfoLayerPool>.CreateValueCallback CreateLayerPool = world => new CellInfoLayerPool(world.Map);
static CellInfoLayerPool LayerPoolForWorld(World world)
{
return LayerPoolTable.GetValue(world, CreateLayerPool);
}
public override IEnumerable<Pair<CPos, int>> Considered
{
get { return considered; }
}
LinkedList<Pair<CPos, int>> considered;
#region Constructors
private PathSearch(IGraph<CellInfo> graph)
: base(graph)
{
considered = new LinkedList<Pair<CPos, int>>();
}
public static IPathSearch Search(World world, Locomotor locomotor, Actor self, BlockedByActor check, Func<CPos, bool> goalCondition)
{
var graph = new PathGraph(LayerPoolForWorld(world), locomotor, self, world, check);
var search = new PathSearch(graph);
search.isGoal = goalCondition;
search.heuristic = loc => 0;
return search;
}
public static IPathSearch FromPoint(World world, Locomotor locomotor, Actor self, CPos @from, CPos target, BlockedByActor check)
{
return FromPoints(world, locomotor, self, new[] { from }, target, check);
}
public static IPathSearch FromPoints(World world, Locomotor locomotor, Actor self, IEnumerable<CPos> froms, CPos target, BlockedByActor check)
{
var graph = new PathGraph(LayerPoolForWorld(world), locomotor, self, world, check);
var search = new PathSearch(graph);
search.heuristic = search.DefaultEstimator(target);
// The search will aim for the shortest path by default, a weight of 100%.
// We can allow the search to find paths that aren't optimal by changing the weight.
// We provide a weight that limits the worst case length of the path,
// e.g. a weight of 110% will find a path no more than 10% longer than the shortest possible.
// The benefit of allowing the search to return suboptimal paths is faster computation time.
// The search can skip some areas of the search space, meaning it has less work to do.
// We allow paths up to 25% longer than the shortest, optimal path, to improve pathfinding time.
search.heuristicWeightPercentage = 125;
search.isGoal = loc =>
{
var locInfo = search.Graph[loc];
return locInfo.EstimatedTotal - locInfo.CostSoFar == 0;
};
foreach (var sl in froms)
if (world.Map.Contains(sl))
search.AddInitialCell(sl);
return search;
}
protected override void AddInitialCell(CPos location)
{
var cost = heuristic(location);
Graph[location] = new CellInfo(0, cost, location, CellStatus.Open);
var connection = new GraphConnection(location, cost);
OpenQueue.Add(connection);
StartPoints.Add(connection);
considered.AddLast(new Pair<CPos, int>(location, 0));
}
#endregion
/// <summary>
/// This function analyzes the neighbors of the most promising node in the Pathfinding graph
/// using the A* algorithm (A-star) and returns that node
/// </summary>
/// <returns>The most promising node of the iteration</returns>
public override CPos Expand()
{
var currentMinNode = OpenQueue.Pop().Destination;
var currentCell = Graph[currentMinNode];
Graph[currentMinNode] = new CellInfo(currentCell.CostSoFar, currentCell.EstimatedTotal, currentCell.PreviousPos, CellStatus.Closed);
if (Graph.CustomCost != null && Graph.CustomCost(currentMinNode) == PathGraph.CostForInvalidCell)
return currentMinNode;
foreach (var connection in Graph.GetConnections(currentMinNode))
{
// Calculate the cost up to that point
var gCost = currentCell.CostSoFar + connection.Cost;
var neighborCPos = connection.Destination;
var neighborCell = Graph[neighborCPos];
// Cost is even higher; next direction:
if (neighborCell.Status == CellStatus.Closed || gCost >= neighborCell.CostSoFar)
continue;
// Now we may seriously consider this direction using heuristics. If the cell has
// already been processed, we can reuse the result (just the difference between the
// estimated total and the cost so far
int hCost;
if (neighborCell.Status == CellStatus.Open)
hCost = neighborCell.EstimatedTotal - neighborCell.CostSoFar;
else
hCost = heuristic(neighborCPos);
var estimatedCost = gCost + hCost;
Graph[neighborCPos] = new CellInfo(gCost, estimatedCost, currentMinNode, CellStatus.Open);
if (neighborCell.Status != CellStatus.Open)
OpenQueue.Add(new GraphConnection(neighborCPos, estimatedCost));
if (Debug)
{
if (gCost > MaxCost)
MaxCost = gCost;
considered.AddLast(new Pair<CPos, int>(neighborCPos, gCost));
}
}
return currentMinNode;
}
}
}