/// <summary>
        /// Computes a heuristic by running a bounded CBS search from the given node.
        /// Assumes g of node was already calculated and h isn't zero.
        /// </summary>
        /// <param name="s"></param>
        /// <param name="targetCost">Stop when the target cost is reached</param>
        /// <param name="sicEstimate">For a debug assertion.</param>
        /// <param name="lowLevelGeneratedCap">The number of low level nodes to generated</param>
        /// <param name="milliCap">The process total millisecond count to stop at</param>
        /// <param name="resume">Whether to resume the last search instead of solving the given node. Assumes the last search was from the same node as the given node.</param>
        /// <returns></returns>
        protected uint h(WorldState s, int targetCost, int sicEstimate = -1, int lowLevelGeneratedCap = -1, int milliCap = int.MaxValue, bool resume = false)
        {
            double start = this.runner.ElapsedMilliseconds();

            ProblemInstance sAsProblemInstance;

            if (resume == false)
            {
                this.cbs.Clear();
                sAsProblemInstance = s.ToProblemInstance(this.instance);
                this.cbs.Setup(sAsProblemInstance,
                               Math.Max(s.makespan,  // This forces must constraints to be upheld when dealing with A*+OD nodes,
                                                     // at the cost of forcing every agent to move when a goal could be found earlier with all must constraints upheld.
                                        s.minDepth), // No point in finding shallower goal nodes
                               this.runner);

                if (this.cbs.openList.Count > 0 && this.cbs.topMost)
                {
                    if (sicEstimate == -1)
                    {
                        sicEstimate = (int)SumIndividualCosts.h(s, this.instance);
                    }
                    Debug.Assert(((CbsNode)this.cbs.openList.Peek()).totalCost - s.g == (int)sicEstimate,
                                 "Total cost of CBS root not same as SIC + g");
                    // Notice we're substracting s.g, not sAsProblemInstance.g.
                    // Must constraints we put may have forced some moves,
                    // and we shouldn't count them as part of the estimate.
                }
            }
            else
            {
                sAsProblemInstance = this.cbs.GetProblemInstance();
            }

            if (lowLevelGeneratedCap == -1)
            {
                // Rough estimate of the branching factor:
                lowLevelGeneratedCap = (int)Math.Pow(Constants.NUM_ALLOWED_DIRECTIONS, this.instance.m_vAgents.Length);
            }

            // Calc the h:
            this.cbs.targetCost           = targetCost;
            this.cbs.milliCap             = milliCap;
            this.cbs.lowLevelGeneratedCap = lowLevelGeneratedCap;

            bool solved = this.cbs.Solve();

            if (solved && this.reportSolution)
            {
                // We're always going to find a proper goal since we respected the node's minDepth
                s.SetSolution(this.cbs.GetSinglePlans());
                s.SetGoalCost(this.cbs.totalCost); // We have to do it explicitly.
                // We can't just change the node's g to g + cbs.totalCost and its h to zero
                // because approaches like BPMX or maximazing PDBs might "fix" the h back.
                // So instead h is bumped to its maximum value when this method returns.
                s.SetSingleCosts(this.cbs.GetSingleCosts());
                this.nodesSolved++;
            }

            double end = this.runner.ElapsedMilliseconds();

            this.totalRuntime += end - start;
            this.nCalls++;

            this.cbs.AccumulateStatistics();
            this.cbs.ClearStatistics();

            if (this.cbs.totalCost < 0) // A timeout is legitimately possible if very little time was left to begin with,
                                        // and a no solution failure may theoretically be possible too.
            {
                return(this.cbs.GetHeuristic().h(s));
            }

            Debug.Assert(this.cbs.totalCost >= s.g, "CBS total cost " + this.cbs.totalCost + " is smaller than starting problem's initial cost " + s.g + "."); // = is allowed since even though this isn't a goal node (otherwise this function won't be called),
                                                                                                                                                               // a non-goal node can have h==0 if a minimum depth is specified, and all agents have reached their
                                                                                                                                                               // goal in this node, but the depth isn't large enough.

            uint cbsEstimate = (uint)(this.cbs.totalCost - s.g);

            // Discounting the moves the agents did before we started solving
            // (This is easier than making a copy of each AgentState just to zero its lastMove.time)

            this.totalImprovement += (int)(cbsEstimate - s.h); // Not computing difference from SIC to not over-count, since a node can be improved twice.
                                                               // Can be negative if the base heuristic was improved by:
                                                               // - Partial expansion
                                                               // - BPMX

            if (validate)
            {
                // Brute-force validation of admissability of estimate:
                var sic = new SumIndividualCosts();
                sic.init(this.instance, this.vAgents);
                var epeastarsic = new AStarWithPartialExpansion(sic);
                epeastarsic.Setup(sAsProblemInstance, s.makespan, runner);
                bool epeastarsicSolved = epeastarsic.Solve();
                if (epeastarsicSolved)
                {
                    Debug.Assert(epeastarsic.totalCost - s.g >= this.cbs.totalCost - s.g, "Inadmissable!!");
                }
            }

            return(cbsEstimate);
        }
Esempio n. 2
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        /// <summary>
        /// Construct with chosen algorithms.
        /// </summary>
        public Run()
        {
            this.watch = Stopwatch.StartNew();

            // Preparing the heuristics:
            heuristics = new List <HeuristicCalculator>();
            var sic = new SumIndividualCosts();

            heuristics.Add(sic);
            var astar                = new ClassicAStar(sic, false, false, 0);  //withNoBias
            var astarWithBias1       = new ClassicAStar(sic, false, false, 1);  //withBias
            var astarWithBias2       = new ClassicAStar(sic, false, false, 2);  //withBias2
            var astarWithBias3       = new ClassicAStar(sic, false, false, 3);  //withBias3
            var astarWithBias4       = new ClassicAStar(sic, false, false, 4);  //withBias 4
            var astarWithBias5       = new ClassicAStar(sic, false, false, 5);  //withBias 5
            var astarWithBias6       = new ClassicAStar(sic, false, false, 6);  //withBias 6
            var astarWithBias7       = new ClassicAStar(sic, false, false, 7);  //withBias 7
            var astarWithDynamicBias = new ClassicAStar(sic, false, false, -1); //withBias -1
            var cbs              = new CBS_LocalConflicts(astar, astar, -1);
            var astar_with_od    = new AStarWithOD(sic);
            var epea             = new AStarWithPartialExpansion(sic);
            var macbsLocal5Epea  = new CBS_LocalConflicts(astar, epea, 5);
            var macbsLocal50Epea = new CBS_LocalConflicts(astar, epea, 50);


            // Preparing the solvers:
            solvers = new List <ISolver>();

            //k-robust 0,1,2, .. , 7

            solvers.Add(new CBS_GlobalConflicts(astar, epea, -1, false, CBS_LocalConflicts.BypassStrategy.BEST_FIT_LOOKAHEAD,
                                                false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 0, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1

            solvers.Add(new CBS_GlobalConflicts(astarWithBias1, epea, -1, false, CBS_LocalConflicts.BypassStrategy.FIRST_FIT_LOOKAHEAD,
                                                false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 1, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1

            solvers.Add(new CBS_GlobalConflicts(astarWithBias2, epea, -1, false, CBS_LocalConflicts.BypassStrategy.FIRST_FIT_LOOKAHEAD,
                                                false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 2, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1

            /*
             * solvers.Add(new CBS_GlobalConflicts(astarWithBias3, epea, -1, false, CBS_LocalConflicts.BypassStrategy.FIRST_FIT_LOOKAHEAD,
             *          false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 3, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1
             *
             * solvers.Add(new CBS_GlobalConflicts(astarWithBias4, epea, -1, false, CBS_LocalConflicts.BypassStrategy.FIRST_FIT_LOOKAHEAD,
             *          false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 4, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1
             *
             * solvers.Add(new CBS_GlobalConflicts(astarWithBias5, epea, -1, false, CBS_LocalConflicts.BypassStrategy.FIRST_FIT_LOOKAHEAD,
             *          false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 5, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1
             *
             * solvers.Add(new CBS_GlobalConflicts(astarWithBias6, epea, -1, false, CBS_LocalConflicts.BypassStrategy.FIRST_FIT_LOOKAHEAD,
             *          false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 6, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1
             *
             * solvers.Add(new CBS_GlobalConflicts(astarWithBias7, epea, -1, false, CBS_LocalConflicts.BypassStrategy.FIRST_FIT_LOOKAHEAD,
             *          false, CBS_LocalConflicts.ConflictChoice.FIRST, false, false, 1, false, 7, ConstraintPolicy.Range)); // CBS/EPEA* + CARDINAL + BP1
             */
            outOfTimeCounters = new int[solvers.Count];
            for (int i = 0; i < outOfTimeCounters.Length; i++)
            {
                outOfTimeCounters[i] = 0;
            }
        }
Esempio n. 3
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        /// <summary>
        /// Construct with chosen algorithms.
        /// </summary>
        public Run()
        {
            this.watch = Stopwatch.StartNew();

            // Preparing the heuristics:
            heuristics = new List <HeuristicCalculator>();
            var sic = new SumIndividualCosts();

            heuristics.Add(sic);
            var astar           = new ClassicAStar(sic);
            var cbs             = new CBS_LocalConflicts(astar, astar, -1);
            var astar_with_od   = new AStarWithOD(sic);
            var epea            = new AStarWithPartialExpansion(sic);
            var macbsLocal5Epea = new CBS_LocalConflicts(astar, epea, 5);
            //var cbsHeuristicNoSolve1 = new CbsHeuristic(cbs, this, false, 1);
            //var cbsHeuristicNoSolve2 = new CbsHeuristic(cbs, this, false, 2);
            //var cbsHeuristicNoSolve3 = new CbsHeuristic(cbs, this, false, 3);
            //var cbsHeuristicNoSolve4 = new CbsHeuristic(cbs, this, false, 4);
            //var cbsHeuristicNoSolve5 = new CbsHeuristic(cbs, this, false, 5);
            //var cbsHeuristicNoSolve6 = new CbsHeuristic(cbs, this, false, 6);
            //var cbsHeuristicSolve1 = new CbsHeuristic(cbs, this, true, 1);
            //var cbsHeuristicSolve2 = new CbsHeuristic(cbs, this, true, 2);
            //var cbsHeuristicSolve3 = new CbsHeuristic(cbs, this, true, 3);
            //var cbsHeuristicSolve4 = new CbsHeuristic(cbs, this, true, 4);
            //var cbsHeuristicSolve5 = new CbsHeuristic(cbs, this, true, 5);
            //var cbsHeuristicSolve6 = new CbsHeuristic(cbs, this, true, 6);
            //var sicOrCbsh6 = new RandomChoiceOfHeuristic(cbsHeuristicSolve6, sic, 1.0 / 5);

            //var dynamicLazyCbsh = new DyanamicLazyCbsh(cbs, this, true);
            //heuristics.Add(dynamicLazyCbsh);

            var dynamicLazyMacbsLocal5EpeaH = new DyanamicLazyCbsh(macbsLocal5Epea, this, true);

            heuristics.Add(dynamicLazyMacbsLocal5EpeaH);

            // Preparing the solvers:
            solvers = new List <ISolver>();

            solvers.Add(new CBS_LocalConflicts(astar, epea, 5)); // Works and is very fast so is a good choice for cost validation
            //solvers.Add(new CBS_GlobalConflicts(astar, astar, -1)); // Should be identical since no merging is done

            /*
             * //solvers.Add(new CBS_LocalConflicts(epea, epea, -1));
             * //solvers.Add(new CBS_GlobalConflicts(epea, epea, -1)); // Should be identical since no merging is done.
             * //solvers.Add(new CBS_LocalConflicts(epea, epea, 0));
             * solvers.Add(new CBS_LocalConflicts(astar, epea, 0));
             * //solvers.Add(new CBS_GlobalConflicts(epea, epea, 0));
             * //solvers.Add(new CBS_LocalConflicts(epea, epea, 1));
             * //solvers.Add(new CBS_GlobalConflicts(epea, epea, 1));
             * //solvers.Add(new CBS_LocalConflicts(epea, epea, 5));
             * solvers.Add(new CBS_LocalConflicts(astar, epea, 5));
             * //solvers.Add(new CBS_GlobalConflicts(epea, epea, 5));
             * //solvers.Add(new CBS_LocalConflicts(epea, epea, 10));
             * solvers.Add(new CBS_LocalConflicts(astar, epea, 10));
             * //solvers.Add(new CBS_GlobalConflicts(epea, epea, 10));
             * //solvers.Add(new CBS_LocalConflicts(epea, epea, 100));
             * solvers.Add(new CBS_LocalConflicts(astar, epea, 100));
             * //solvers.Add(new CBS_GlobalConflicts(epea, epea, 100));
             * //solvers.Add(new CBS_LocalConflicts(epea, epea, 500));
             * //solvers.Add(new CBS_GlobalConflicts(epea, epea, 500));
             *
             * //solvers.Add(new CBS_LocalConflicts(astar_with_od, astar_with_od, -1));
             * //solvers.Add(new CBS_GlobalConflicts(astar_with_od, astar_with_od, -1)); // Should be identical since no merging is done.
             * //solvers.Add(new CBS_LocalConflicts(astar_with_od, astar_with_od, 0));
             * solvers.Add(new CBS_LocalConflicts(astar, astar_with_od, 0));
             * //solvers.Add(new CBS_GlobalConflicts(astar_with_od, astar_with_od, 0));
             * //solvers.Add(new CBS_LocalConflicts(astar_with_od, astar_with_od, 1));
             * //solvers.Add(new CBS_GlobalConflicts(astar_with_od, astar_with_od, 1));
             * //solvers.Add(new CBS_LocalConflicts(astar_with_od, astar_with_od, 5));
             * solvers.Add(new CBS_LocalConflicts(astar, astar_with_od, 5));
             * //solvers.Add(new CBS_GlobalConflicts(astar_with_od, astar_with_od, 5));
             * //solvers.Add(new CBS_LocalConflicts(astar_with_od, astar_with_od, 10));
             * solvers.Add(new CBS_LocalConflicts(astar, astar_with_od, 10));
             * //solvers.Add(new CBS_GlobalConflicts(astar_with_od, astar_with_od, 10));
             * //solvers.Add(new CBS_LocalConflicts(astar_with_od, astar_with_od, 100));
             * solvers.Add(new CBS_LocalConflicts(astar, astar_with_od, 100));
             * //solvers.Add(new CBS_GlobalConflicts(astar_with_od, astar_with_od, 100));
             * //solvers.Add(new CBS_LocalConflicts(astar_with_od, astar_with_od, 500));
             * //solvers.Add(new CBS_GlobalConflicts(astar_with_od, astar_with_od, 500));
             */
            //solvers.Add(new ClassicAStar(sic)); // Works
            //solvers.Add(new ClassicAStar(cbsHeuristic)); // Works
            //solvers.Add(new AStarWithOD(sic));  // Works
            //solvers.Add(new AStarWithPartialExpansionBasic(sic)); // Works
            //solvers.Add(new AStarWithPartialExpansionBasic(cbsHeuristic));
            solvers.Add(new AStarWithPartialExpansion(sic));     // Works.
            solvers.Add(new CBS_LocalConflicts(astar, epea, 0)); // EPEA*+(S)ID

            //solvers.Add(new ClassicAStar(cbsHeuristicSolve1));
            //solvers.Add(new ClassicAStar(cbsHeuristicSolve2));
            //solvers.Add(new ClassicAStar(cbsHeuristicSolve3));
            //solvers.Add(new ClassicAStar(cbsHeuristicSolve4));
            //solvers.Add(new ClassicAStar(cbsHeuristicSolve5));
            //solvers.Add(new ClassicAStar(cbsHeuristicSolve6));
            //solvers.Add(new ClassicAStar(cbsHeuristicNoSolve1));
            //solvers.Add(new ClassicAStar(cbsHeuristicNoSolve2));
            //solvers.Add(new ClassicAStar(cbsHeuristicNoSolve3));
            //solvers.Add(new ClassicAStar(cbsHeuristicNoSolve4));
            //solvers.Add(new ClassicAStar(cbsHeuristicNoSolve5));
            //solvers.Add(new ClassicAStar(cbsHeuristicNoSolve6));
            //solvers.Add(new ClassicAStar(sicOrCbsh6));

            //solvers.Add(new AStarWithOD(cbsHeuristicSolve1));
            //solvers.Add(new AStarWithOD(cbsHeuristicSolve2));
            //solvers.Add(new AStarWithOD(cbsHeuristicSolve3));
            //solvers.Add(new AStarWithOD(cbsHeuristicSolve4));
            //solvers.Add(new AStarWithOD(cbsHeuristicSolve5));
            //solvers.Add(new AStarWithOD(cbsHeuristicSolve6));
            //solvers.Add(new AStarWithOD(cbsHeuristicNoSolve1));
            //solvers.Add(new AStarWithOD(cbsHeuristicNoSolve2));
            //solvers.Add(new AStarWithOD(cbsHeuristicNoSolve3));
            //solvers.Add(new AStarWithOD(cbsHeuristicNoSolve4));
            //solvers.Add(new AStarWithOD(cbsHeuristicNoSolve5));
            //solvers.Add(new AStarWithOD(cbsHeuristicNoSolve6));
            //solvers.Add(new AStarWithOD(sicOrCbsh6));

            ClassicAStar solver;

            // dynamic not rational lazy A*+OD/CBS/A*/SIC:
            //solver = new AStarWithOD(sic);
            //var dynamicLazyOpenList1 = new DynamicLazyOpenList(solver, dynamicLazyCbsh, this);
            //solver.openList = dynamicLazyOpenList1;
            //solvers.Add(solver);

            // dynamic rational lazy A*+OD/CBS/A*/SIC:
            //solver = new AStarWithOD(sic);
            //var dynamicRationalLazyOpenList1 = new DynamicRationalLazyOpenList(solver, dynamicLazyCbsh, this);
            //solver.openList = dynamicRationalLazyOpenList1;
            //solvers.Add(solver);

            // dynamic rational lazy MA-CBS-local-5/A*+OD/MA-CBS-local-5/EPEA*/SIC:
            //solver = new AStarWithOD(sic);
            //var dynamicRationalLazyOpenList3 = new DynamicRationalLazyOpenList(solver, dynamicLazyMacbsLocal5EpeaH, this);
            //solver.openList = dynamicRationalLazyOpenList3;
            //solvers.Add(new CBS_LocalConflicts(astar, solver, 5));

            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicSolve1));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicSolve2));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicSolve3));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicSolve4));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicSolve5));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicSolve6));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicNoSolve1));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicNoSolve2));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicNoSolve3));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicNoSolve4));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicNoSolve5));
            //solvers.Add(new AStarWithPartialExpansion(cbsHeuristicNoSolve6));
            //solvers.Add(new AStarWithPartialExpansion(sicOrCbsh6));

            // dynamic not rational lazy EPEA*/CBS/A*/SIC:
            //solver = new AStarWithPartialExpansion(sic);
            //var dynamicLazyOpenList2 = new DynamicLazyOpenList(solver, dynamicLazyCbsh, this);
            //solver.openList = dynamicLazyOpenList2;
            //solvers.Add(solver);

            // dynamic rational lazy EPEA*/CBS/A*/SIC:
            //solver = new AStarWithPartialExpansion(sic);
            //var dynamicRationalLazyOpenList2 = new DynamicRationalLazyOpenList(solver, dynamicLazyCbsh, this);
            //solver.openList = dynamicRationalLazyOpenList2;
            //solvers.Add(solver);

            // MA-CBS-local-5/dynamic rational lazy EPEA*/MA-CBS-local-5/EPEA*/SIC:
            solver = new AStarWithPartialExpansion(sic);
            var dynamicRationalLazyOpenList4 = new DynamicRationalLazyOpenList(solver, dynamicLazyMacbsLocal5EpeaH, this);

            solver.openList = dynamicRationalLazyOpenList4;
            solvers.Add(new CBS_LocalConflicts(astar, solver, 5));

            // dynamic rational lazy EPEA*/MA-CBS-local-5/EPEA*/SIC + (S)ID:
            solver = new AStarWithPartialExpansion(sic);
            var dynamicRationalLazyOpenList6 = new DynamicRationalLazyOpenList(solver, dynamicLazyMacbsLocal5EpeaH, this);

            solver.openList = dynamicRationalLazyOpenList6;
            solvers.Add(new CBS_LocalConflicts(astar, solver, 0));

            // dynamic rational lazy EPEA*/MA-CBS-local-5/EPEA*/SIC:
            solver = new AStarWithPartialExpansion(sic);
            var dynamicRationalLazyOpenList8 = new DynamicRationalLazyOpenList(solver, dynamicLazyMacbsLocal5EpeaH, this);

            solver.openList = dynamicRationalLazyOpenList8;
            solvers.Add(solver);

            //solvers.Add(new CostTreeSearchSolverNoPruning());
            //solvers.Add(new CostTreeSearchSolverKMatch(2));
            //solvers.Add(new CostTreeSearchSolverOldMatching(2));
            //solvers.Add(new CostTreeSearchSolverRepatedMatch(2));
            //solvers.Add(new CostTreeSearchSolverKMatch(3));
            //solvers.Add(new CostTreeSearchSolverOldMatching(3));
            //solvers.Add(new CostTreeSearchSolverRepatedMatch(3));

            //solvers.Add(new CostTreeSearchNoPruning());
            //solvers.Add(new CostTreeSearchKMatch(2));
            //solvers.Add(new CostTreeSearchOldMatching(2));
            //solvers.Add(new CostTreeSearchRepatedMatch(2));
            //solvers.Add(new CostTreeSearchKMatch(3));
            //solvers.Add(new CostTreeSearchOldMatching(3));
            //solvers.Add(new CostTreeSearchRepatedMatch(3));

            //solvers.Add(new Trevor(new AStarWithPartialExpansion()));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new AStarWithPartialExpansion(), 1, 1)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new AStarWithPartialExpansion(), 5, 5)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new AStarWithPartialExpansion(), 10, 10)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new AStarWithPartialExpansion(), 100, 100)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new AStarWithPartialExpansion(), 500, 500)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new ClassicAStar())));

            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new ClassicAStar(), 1, 1)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new ClassicAStar(), 5, 5)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new ClassicAStar(), 10, 10)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new ClassicAStar(), 100, 100)));
            //solvers.Add(new Trevor(new CBS_GlobalConflicts(new ClassicAStar(), 500, 500)));

            //solvers.Add(new Trevor(new AStarWithPartialExpansionBasic()));
            //solvers.Add(new Trevor(new AStarWithPartialExpansion()));
            //solvers.Add(new Trevor(new ClassicAStar()));
            //solvers.Add(new Trevor());

            //solvers.Add(new CBS_IDA(new ClassicAStar())); // Don't run! Uses must conds

            //solvers.Add(new CBS_GlobalConflicts(new ClassicAStar())); // Works

            //solvers.Add(new CBS_NoDD(new ClassicAStar()));
            //solvers.Add(new CBS_NoDDb3(new ClassicAStar()));
            //solvers.Add(new CBS_GlobalConflicts(new ClassicAStar(), 1, 1)); // Run this!

            outOfTimeCounters = new int[solvers.Count];
            for (int i = 0; i < outOfTimeCounters.Length; i++)
            {
                outOfTimeCounters[i] = 0;
            }
        }