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);
}
public Plan(Domain d, PlanEvaluator ev)
{
this.actions = new List <int>();
this.dom = d;
this.ev = ev;
}
