source: branches/HeuristicLab.Problems.GrammaticalOptimization/HeuristicLab.Algorithms.MonteCarloTreeSearch/MonteCarloTreeSearch_PruneLeaves.cs @ 12829

using System.Diagnostics;
using HeuristicLab.Algorithms.Bandits;
using HeuristicLab.Algorithms.MonteCarloTreeSearch.Base;
using HeuristicLab.Algorithms.MonteCarloTreeSearch.Simulation;
using HeuristicLab.Problems.GrammaticalOptimization;
using System;
using System.Linq;
using System.Threading;

namespace HeuristicLab.Algorithms.MonteCarloTreeSearch
{
    public class MonteCarloTreeSearch_PruneLeaves : MonteCarloTreeSearch
    {
        public MonteCarloTreeSearch_PruneLeaves(ISymbolicExpressionTreeProblem problem, int maxLen, Random random, IBanditPolicy behaviourPolicy,
            ISimulation simulationPolicy)
            : base(problem, maxLen, random, behaviourPolicy, simulationPolicy)
        {
        }

        public override void Run(int maxIterations)
        {
            Reset();
            int selections = 0;
            TreeNode currentNode;
            string phrase;
            string simulatedPhrase;
            double quality;
            for (int i = 0; !StopRequested && i < maxIterations; i++)
            {
                currentNode = rootNode;

                while (!currentNode.IsLeaf())
                {
                    int currentActionIndex = behaviourPolicy.SelectAction(random,
                        currentNode.GetChildActionInfos());
                    currentNode = currentNode.children[currentActionIndex];
                    //selections++;
                    //CheckSelection(currentNode, selections);
                }

                phrase = currentNode.phrase;

                if (phrase.Length <= maxLen)
                {
                    // Version 2:
                    if (currentNode.children != null && !currentNode.children.Any())
                    {
                        // already removed all child nodes so remove it too..
                        currentNode.parent.children.Remove(currentNode);
                        continue;
                    }
                    ExpandTreeNode(currentNode);
                    if (currentNode.children.Any())
                    {
                        currentNode =
                            currentNode.children[behaviourPolicy.SelectAction(random, currentNode.GetChildActionInfos())
                                ];
                        //selections++;
                        //CheckSelection(currentNode, selections);
                    }
                    else
                    {
                        // Version 2:
                        // remove currentNode from tree..
                        currentNode.parent.children.Remove(currentNode);
                    }
                }
                if (currentNode.phrase.Length <= maxLen)
                {
                    quality = simulation.Simulate(currentNode, out simulatedPhrase);
                    OnSolutionEvaluated(simulatedPhrase, quality);

                    Propagate(currentNode, quality);
                }
            }
        }
    }
}