最快的跨平台 A* 实现? [英] Fastest cross-platform A* implementation?

问题描述

有这么多可用的实现，使用小网格的 C++ 执行速度最快(CPU 占用最少、二进制最小)、跨平台(Linux、Mac、Windows、iPhone)A* 实现是什么?

With so many implementations available, what is the fastest executing (least CPU intensive, smallest binary), cross-platform (Linux, Mac, Windows, iPhone) A* implementation for C++ using a small grid?

实施

谷歌返回:

• http://www.heyes-jones.com/astar.html(该网站上的大多数链接都已失效.)
• http://www.grinninglizard.com/MicroPather(据说比 Heyes-琼斯.)
• http://www.ceng.metu.edu.tr/~cuneyt/codes.html(通用 C++ 代码.)
• http://swampthingtom.blogspot.com/2007/07/pathfinding-sample-using.html
• http://opensteer.sourceforge.net/(对游戏很感兴趣，不是 A*.)
• Dijkstra 算法的堆栈溢出

• http://www.heyes-jones.com/astar.html (Most links on that site are dead.)
• http://www.grinninglizard.com/MicroPather (Said to be slower than Heyes-Jones'.)
• http://www.ceng.metu.edu.tr/~cuneyt/codes.html (Generic C++ code.)
• http://swampthingtom.blogspot.com/2007/07/pathfinding-sample-using.html
• http://opensteer.sourceforge.net/ (Interesting for games, not A*.)
• Stack Overflow on Dijkstra's Algorithm

还有其他的吗?

轮子

正如所问的那样，这个问题与重用(插入游戏)有关，而不是重新发明(至少在性能被证明是一个问题之前).事实证明，Dijkstra 实现(或通用寻路算法)更适合，或者最快的实现不够快.我很欣赏替代算法的建议，但问题不是，我应该推出自己的 A* 吗?"

The question, as asked, pertains to reuse (plug into a game), not reinvention (at least not until performance is shown to be an issue). It might turn out that a Dijkstra implementation (or generic pathfinding algorithm) is better suited, or that the fastest implementations are not fast enough. I appreciate the suggestions of alternative algorithms, however the question is not, "Should I roll my own A*?"

• 乔尔谈软件 - 并非发明在这里综合症
• 编码恐怖:不要重新发明轮子
• 克服非发明"此处综合症"

推荐答案

查看其他寻路算法(如 Breath-First、Depth-First、Minimax、Negmax 等)并权衡您的场景的正面和负面.

Look at other path-finding algorithms (like Breath-First, Depth-First, Minimax, Negmax etc.) and weigh the positives and negatives for your scenario.

Boost 也有一个A-star实施.尝试按照这些说明在 iPhone 上构建提升，但它可能不适合您:它不是 boost 的完整端口"，它可能会出错.

Boost also has an A-star implementation. Try following these instructions to build boost on iPhone, but it might not work for you: it is not a "full port" of boost and it might error out.

以下内容来自 算法简述(Java，不是 C++，但也许你喜欢移植它):

The following is from Algorithms in a Nutshell (Java, not C++ but maybe you'd like to port it):

public Solution search( INode initial, INode goal ) {
  // Start from the initial state
  INodeSet open = StateStorageFactory.create( StateStorageFactory.TREE );
  INode copy = initial.copy();
  scoringFunction.score( copy );
  open.insert( copy );

  // Use Hashtable to store states we have already visited.
  INodeSet closed = StateStorageFactory.create( StateStorageFactory. HASH );
  while( !open.isEmpty() ) {
    // Remove node with smallest evaluation function and mark closed.
    INode n = open.remove();

    closed.insert( n );

    // Return if goal state reached.
    if( n.equals( goal ) ) { return new Solution( initial, n ); }

    // Compute successor moves and update OPEN/CLOSED lists.
    DepthTransition trans = (DepthTransition)n.storedData();
    int depth = 1;

    if( trans ! = null ) { depth = trans.depth + 1; }

    DoubleLinkedList<IMove> moves = n.validMoves();

    for( Iterator<IMove> it = moves.iterator(); it.hasNext(); ) {
      IMove move = it.next();

      // Make move and score the new board state.
      INode successor = n.copy();
      move.execute( successor );

      // Record previous move for solution trace and compute
      // evaluation function to see if we have improved upon
      // a state already closed
      successor.storedData( new DepthTransition( move, n, depth ) );
      scoringFunction.score( successor );

      // If already visited, see if we are revisiting with lower
      // cost. If not, just continue; otherwise, pull out of closed
      // and process
      INode past = closed.contains( successor );

      if( past ! = null ) {
        if( successor.score() >= past.score() ) {
          continue;
        }

        // we revisit with our lower cost.
        closed.remove( past );
      }

      // place into open.
      open.insert( successor );
    }
  }

  // No solution.
  return new Solution( initial, goal, false );
}

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