public void TC_WeightedHeuristic()
{
var sasProblem = new Planner.SAS.Problem(new SASInputData(GetFilePath("TC_Gripper.sas")));
var pddlProblem = new Planner.PDDL.Problem(new PDDLInputData(GetFilePath("TC_Gripper_D.pddl"), GetFilePath("TC_Gripper_P.pddl")));
var heuristic = new WeightedHeuristic(new StripsHeuristic(sasProblem), 3);
Assert.AreEqual(12, heuristic.GetValue(sasProblem.GetInitialState()));
Assert.AreEqual(12, heuristic.GetValue(new Planner.SAS.State(0, 0, 0, 0, 0, 0, 0)));
Assert.AreEqual(6, heuristic.GetValue(new Planner.SAS.State(0, 1, 1, 0, 0, 0, 0)));
Assert.AreEqual(0, heuristic.GetValue(new Planner.SAS.State(1, 1, 1, 1, 0, 0, 0)));
Assert.AreEqual(12, heuristic.GetValue(sasProblem.GetGoalConditions()));
Assert.AreEqual(12, heuristic.GetValue(sasProblem.GetGoalConditions().GetCorrespondingRelativeStates(sasProblem).First()));
Assert.AreEqual("Weighted STRIPS Heuristic (weight = 3)", heuristic.GetName());
Assert.AreEqual(6, heuristic.GetCallsCount());
var heuristic2 = new WeightedHeuristic(new StripsHeuristic(pddlProblem), 9);
Assert.AreEqual(18, heuristic2.GetValue(pddlProblem.GetInitialState()));
Assert.AreEqual(18, heuristic2.GetValue(pddlProblem.GetGoalConditions()));
Assert.AreEqual(18, heuristic2.GetValue(pddlProblem.GetGoalConditions().GetCorrespondingRelativeStates(pddlProblem).First()));
Assert.AreEqual("Weighted STRIPS Heuristic (weight = 9)", heuristic2.GetName());
Assert.AreEqual(3, heuristic2.GetCallsCount());
}
public MCTSSolver(Domain dom, Heuristic h)
{
this.dom = dom;
this.h = h;
this.root = TreeNode.createRoot(dom.initialState);
TreeNode.dom = dom;
TreeNode.solver = this;
//TODO only 1 MCTS solver may run at the same time!!
bestPlan = null;
bestValue = int.MaxValue;
//this.perfoHeuristic = new BestPerformancePolicy(dom);
this.maxSimulationLength = 50;
//Heuristic simulationHeuristic = new WeightedHeuristic(new NotAccomplishedGoalCount(dom), 10);
Heuristic simulationHeuristic = new WeightedHeuristic(new FFHeuristic(dom), 10);
//this.simulationPolicy = new RandomSimulationPolicy(dom, maxSimulationLength);
//this.simulationPolicy = new HeuristicGreedySearch(new NotAccomplishedGoalCount(dom), dom, maxSimulationLength);
//this.simulationPolicy = new HeuristicGreedySearch(new FFHeuristic(dom), dom, maxSimulationLength);
//this.simulationPolicy = new AStarSimulationPolicy(simulationHeuristic, dom, maxSimulationLength);
//this.simulationPolicy = new F_LimitedAStarSimulationPolicy(simulationHeuristic, dom, maxSimulationLength, 2 * maxSimulationLength);
//this.simulationPolicy = new BeamSearchPolicy(simulationHeuristic, dom, 2);
CompositeSimulationPolicy policy = new CompositeSimulationPolicy();
policy.addPolicy(new RandomSimulationPolicy(dom, maxSimulationLength));
policy.addPolicy(new HeuristicGreedySearch(new FFHeuristic(dom), dom, maxSimulationLength));
policy.addPolicy(new AStarSimulationPolicy(simulationHeuristic, dom, maxSimulationLength));
policy.addPolicy(new BeamSearchPolicy(simulationHeuristic, dom, 2));
this.simulationPolicy = policy;
this.ev = new HeuristicPlanEvaluator(dom, h, maxSimulationLength);
}
