/// <summary>
/// Determines how many additive pattern databases to build and divides
/// the agents among them, possibly leaving some agents out.
/// </summary>
/// <param name="pi">the problem instance to use</param>
/// <param name="s">The root of the search tree. This is also expected
/// to have context parameters such as agents' goal states.</param>
public void build(ProblemInstance pi, WorldState s)
{
Debug.Write("Building database...");
// As a simple rule, we'll simply take pairs of agents starting
// with the first two, then the second two, etc.
PDBs = new List <PDB>();
if (s.allAgentsState.Length > 1)
{
for (uint i = 0; i < s.allAgentsState.Length - 1; i += 2)
{
// Make a list of agents we want to include together in the
// next additive pattern database. We specify agents by
// their index into the WorldState.allAgentsState
// array.
List <uint> agentsToConsider = new List <uint>();
agentsToConsider.Add(i);
agentsToConsider.Add(i + 1);
// Create a new root search node where the state only
// includes a subset of the agents of the original search
// node. This is done by passing into the state copy
// constructor our list of important agents.
WorldState tws = new WorldState(s.allAgentsState, agentsToConsider);
// Initialize, build, and save the new pattern database.
EnumeratedPDB pdb = new EnumeratedPDB();
pdb.Init(pi, agentsToConsider);
pdb.build();
Debug.Write(".");
PDBs.Add(pdb);
}
}
// Create single shortest path pattern database heuristics for the
// remaining agents if we have any left over.
if (s.allAgentsState.Length % 2 == 1)
{
SumIndividualCosts pdb = new SumIndividualCosts();
List <uint> agentsToConsider = new List <uint>(1);
agentsToConsider.Add((uint)s.allAgentsState.Length - 1);
pdb.Init(pi, agentsToConsider);
pdb.build();
PDBs.Add(pdb);
}
// For informational purposes, we will set the number of agents
// that aren't included in this set of pattern databases.
excludedAgents = new SortedSet <uint>();
Debug.WriteLine("done.");
}
/// <summary>
/// This is the starting point of the program.
/// </summary>
static void Main(string[] args)
{
Program me = new Program();
Program.RESULTS_FILE_NAME = Process.GetCurrentProcess().ProcessName + ".csv";
if (System.Diagnostics.Debugger.IsAttached)
{
Constants.MAX_TIME = int.MaxValue;
Debug.WriteLine("Debugger attached - running without a timeout!!");
}
if (Directory.Exists(Path.Combine(Directory.GetCurrentDirectory(), "..", "..", "Instances")) == false)
{
Directory.CreateDirectory(Path.Combine(Directory.GetCurrentDirectory(), "..", "..", "Instances"));
}
Program.onlyReadInstances = false;
int instances = 100;
bool runGrids = false;
bool runDragonAge = false;
bool runMazesWidth1 = false;
bool runSpecific = false;
bool runPaperProblems = false;
bool runPaperProblemsIncrementally = false; // Turn on for CA*
if (runGrids == true)
{
//int[] gridSizes = new int[] { 8, };
//int[] agentListSizes = new int[] { 2, 3, 4 };
//int[] gridSizes = new int[] { 6, };
//int[] agentListSizes = new int[] { /*2,*/ 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32 };
// Note that success rate drops almost to zero for EPEA* and A*+OD/SIC on 40 agents.
int[] gridSizes = new int[] { 20, };
//int[] agentListSizes = new int[] { 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, /*60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150*/ };
int[] agentListSizes = new int[] { 40, 60, 80, 100 };
//int[] obstaclesPercents = new int[] { 20, };
//int[] obstaclesPercents = new int[] { /*0, 5, 10, 15, 20, 25, 30, 35, */20, 30, 40};
int[] obstaclesPercents = new int[] { /*0, 5, 10,*/ 15, /*20, 25, 30, 35, 20, 30, 40*/ };
me.RunExperimentSet(gridSizes, agentListSizes, obstaclesPercents, instances);
}
else if (runDragonAge == true)
{
me.RunDragonAgeExperimentSet(instances, Program.daoMapPaths); // Obstacle percents and grid sizes built-in to the maps.
}
else if (runMazesWidth1 == true)
{
me.RunDragonAgeExperimentSet(instances, Program.mazeMapPaths); // Obstacle percents and grid sizes built-in to the maps.
}
else if (runSpecific == true)
{
ProblemInstance instance;
try
{
if (args[0].EndsWith(".dll"))
{
instance = ProblemInstance.Import(args[2], args[1]);
}
else
{
instance = ProblemInstance.Import(args[1], args[0]);
}
}
catch (Exception e)
{
Console.WriteLine($"Bad problem instance {args[1]}. Error: {e.Message}");
return;
}
Run runner = new Run(); // instantiates stuff unnecessarily
runner.startTime = runner.ElapsedMillisecondsTotal();
IHeuristicCalculator <WorldState> lowLevelHeuristic = new SumIndividualCosts();
List <uint> agentList = Enumerable.Range(0, instance.agents.Length).Select(x => (uint)x).ToList(); // FIXME: Must the heuristics really receive a list of uints?
lowLevelHeuristic.Init(instance, agentList);
ICbsSolver lowLevel = new A_Star(lowLevelHeuristic);
ILazyHeuristic <CbsNode> highLevelHeuristic = new MvcHeuristicForCbs();
highLevelHeuristic.Init(instance, agentList);
// ISolver solver = new CBS(lowLevel, lowLevel,
// bypassStrategy: CBS.BypassStrategy.FIRST_FIT_LOOKAHEAD,
// conflictChoice: CBS.ConflictChoice.CARDINAL_MDD,
// heuristic: highLevelHeuristic,
// cacheMdds: true,
// useOldCost: true,
// replanSameCostWithMdd: true
// );
//ISolver solver = new IndependenceDetection(lowLevel, new EPEA_Star(lowLevelHeuristic));
//ISolver solver = new IndependenceDetection(lowLevel, new CostTreeSearchSolverOldMatching(3));
ISolver solver = new IndependenceDetection(lowLevel, new A_Star_WithOD(lowLevelHeuristic));
solver.Setup(instance, runner);
bool solved = solver.Solve();
if (solved == false)
{
Console.WriteLine("Failed to solve");
return;
}
Plan plan = solver.GetPlan();
plan.PrintPlan();
//me.RunInstance("Instance-5-15-3-792");
//me.RunInstance("Instance-5-15-3-792-4rows");
//me.RunInstance("Instance-5-15-3-792-3rows");
//me.RunInstance("Instance-5-15-3-792-2rows");
//me.RunInstance("corridor1");
//me.RunInstance("corridor2");
//me.RunInstance("corridor3");
//me.RunInstance("corridor4");
return;
}
else if (runPaperProblems)
{
foreach (var dirName in scenDirs)
{
foreach (var scenPath in Directory.GetFiles(dirName))
{
var problem = ProblemInstance.Import(scenPath);
foreach (var numAgents in Enumerable.Range(1, problem.agents.Length))
{
var subProblem = problem.Subproblem(problem.agents.Take(numAgents).ToArray());
// don't create a subproblem, just feed time adding one agent and report the sum of times so far
Run runner = new Run();
using (runner)
{
bool resultsFileExisted = File.Exists(RESULTS_FILE_NAME);
runner.OpenResultsFile(RESULTS_FILE_NAME);
if (resultsFileExisted == false)
{
runner.PrintResultsFileHeader();
}
bool success = runner.SolveGivenProblem(subProblem);
if (success == false)
{
break;
}
}
}
}
}
}
else if (runPaperProblemsIncrementally)
{
foreach (var dirName in scenDirs)
{
foreach (var scenPath in Directory.GetFiles(dirName))
{
var problem = ProblemInstance.Import(scenPath);
CooperativeAStar castar = new CooperativeAStar();
Run runner = new Run();
using (runner)
{
bool resultsFileExisted = File.Exists(RESULTS_FILE_NAME);
runner.OpenResultsFile(RESULTS_FILE_NAME);
if (resultsFileExisted == false)
{
runner.PrintResultsFileHeader();
}
runner.SolveGivenProblemIncrementally(problem);
}
}
}
}
// A function to be used by Eric's PDB code
//me.runForPdb();
Console.WriteLine("*********************THE END**************************");
Console.ReadLine();
}
