예제 #1
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 public MinMaxAlphaBeta(int max, IHeuristicFunction heuristicFunction)
 {
     _heuristicFunction = heuristicFunction;
     if (max == 0)
         _max = 1;
     _max = (max * 2) - 1;
 }
예제 #2
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 public SearchProblem(IGoalTest <S> goalTest, IStepCostFunction <A, S, C> stepCost, ISuccessorFunction <A, S> successor, IHeuristicFunction <S, C> heuristicFn)
 {
     this.goalTest    = goalTest;
     this.stepCost    = stepCost;
     this.successorFn = successor;
     this.heuristicFn = heuristicFn;
 }
예제 #3
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파일: MinMax.cs 프로젝트: nickxbs/IA
 public MinMax(int max)
 {
     _heuristicFunction = new HeuristicFunctionDescnedent();
     if (max == 0)
         _max = 1;
     _max = (max * 2) - 1;
 }
예제 #4
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 public MinMax(int max)
 {
     _heuristicFunction = new HeuristicFunctionDescnedent();
     if (max == 0)
     {
         _max = 1;
     }
     _max = (max * 2) - 1;
 }
예제 #5
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 public MinMaxAlphaBeta(int max, IHeuristicFunction heuristicFunction)
 {
     _heuristicFunction = heuristicFunction;
     if (max == 0)
     {
         _max = 1;
     }
     _max = (max * 2) - 1;
 }
예제 #6
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 public MinMaxAlphaBetaWithOpen(int max, IHeuristicFunction heuristicFunction)
     : base(max, heuristicFunction)
 {
 }
예제 #7
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 public HillClimbingSearch(IHeuristicFunction hf)
 {
     this.hf = hf;
 }
 public GreedyBestFirstEvaluationFunction(IHeuristicFunction hf)
 {
     this.hf = hf;
 }
예제 #9
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 public LRTAStarAgent(OnlineSearchProblem problem, IPerceptToStateFunction ptsFunction, IHeuristicFunction hf)
 {
     this.Problem = problem;
     this.PerceptToStateFunction = ptsFunction;
     this.HeuristicFunction      = hf;
 }
예제 #10
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 public SimulatedAnnealingSearch(IHeuristicFunction hf)
 {
     this.hf        = hf;
     this.scheduler = new Scheduler();
 }
예제 #11
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 public SimulatedAnnealingSearch(IHeuristicFunction hf, Scheduler scheduler)
 {
     this.hf        = hf;
     this.scheduler = scheduler;
 }
예제 #12
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 public AStarSearch(IHeuristicFunction <TProblemState> heuristicFunction)
 {
     _heuristicFunction = heuristicFunction;
 }
예제 #13
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 public AStarSearch( Problem problem, IHeuristicFunction heuristic )
 {
     this.m_problem = problem;
     this.m_heuristic = heuristic;
 }
예제 #14
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 public RecursiveBestFirstSearch(IHeuristicFunction heuristicFn)
 {
     _heuristicFn = heuristicFn ?? throw new ArgumentNullException(nameof(heuristicFn));
 }
예제 #15
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 public AStarSearch(QueueSearch search, IHeuristicFunction hf) : base(search, new AStarEvaluationFunction(hf))
 {
 }
예제 #16
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 public MinMaxAlphaBetaWithOpen(int max, IHeuristicFunction heuristicFunction)
     : base(max, heuristicFunction)
 {
 }
 public RecursiveBestFirstSearch(IHeuristicFunction <TProblemState> heuristicFunction)
 {
     _heuristicFunction = heuristicFunction;
 }
예제 #18
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 /// <summary>
 /// Initializes a new instance of the <see cref="HeuristicSearch"/> class.
 /// </summary>
 public HeuristicSearch()
 {
     _queue         = new PriorityQueue <double, Node>();
     this.Heuristic = new Heuristic();
 }
 public GreedyBestFirstSearch(QueueSearch search, IHeuristicFunction hf) : base(search, new GreedyBestFirstEvaluationFunction(hf))
 {
 }
예제 #20
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 public AStarEvaluationFunction(IHeuristicFunction hf)
 {
     this.hf = hf;
 }