生成迷宫的好算法是什么?

发布于 2024-07-05 21:47:43 字数 1835 浏览 14 评论 0原文

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挽清梦 2024-07-12 21:47:43

来自http://www.astrolog.org/labyrnth/algrithm.htm

递归回溯器:这与下面描述的递归回溯器求解方法有些关系,并且需要堆栈达到迷宫的大小。 雕刻时,尽可能贪婪,如果当前单元格旁边有一个未制作的部分,则始终雕刻到未制作的部分。 每次移动到新单元格时,将前一个单元格压入堆栈。 如果当前位置旁边没有未制作的单元格,则将堆栈弹出到上一个位置。 当您从堆栈中弹出所有内容时,迷宫就完成了。 该算法导致迷宫具有尽可能高的“河流”系数,死胡同更少但更长,并且通常是非常长且曲折的解决方案。 它运行得相当快,尽管 Prim 的算法要快一些。 递归回溯不能用作墙加法器,因为这样做往往会导致沿着外部边缘的解决方案路径,其中迷宫的整个内部通过单个茎连接到边界。

它们仅产生 10% 的死胡同

是该方法生成的迷宫的示例。

From http://www.astrolog.org/labyrnth/algrithm.htm

Recursive backtracker: This is somewhat related to the recursive backtracker solving method described below, and requires stack up to the size of the Maze. When carving, be as greedy as possible, and always carve into an unmade section if one is next to the current cell. Each time you move to a new cell, push the former cell on the stack. If there are no unmade cells next to the current position, pop the stack to the previous position. The Maze is done when you pop everything off the stack. This algorithm results in Mazes with about as high a "river" factor as possible, with fewer but longer dead ends, and usually a very long and twisty solution. It runs quite fast, although Prim's algorithm is a bit faster. Recursive backtracking doesn't work as a wall adder, because doing so tends to result in a solution path that follows the outside edge, where the entire interior of the Maze is attached to the boundary by a single stem.

They produce only 10% dead ends

is an example of a maze generated by that method.

二智少女 2024-07-12 21:47:43

一个非常简单的解决方案可能是为图的边缘分配随机权重,并应用 Kruskal 算法找到最小生成树。

关于迷宫生成算法的最佳讨论:http://www.jamisbuck.org/presentations/rubyconf2011 /index.html(几天前在 HN 上)。

A pretty straightforward solution could be to assign random weights to the graph edges and apply Kruskal's algorithm to find a minimum spanning tree.

Best discussion ever on maze generation algorithms: http://www.jamisbuck.org/presentations/rubyconf2011/index.html (was on HN a couple days ago).

滥情哥ㄟ 2024-07-12 21:47:43

我最喜欢的方法是使用 Kruskal 算法,但是当随机选择并删除边缘时,根据其连接的边缘类型对选择进行加权。

通过改变不同边缘类型的权重,您可以生成具有许多不同特征或“个性”的迷宫。 请参阅我的示例:

https://mtimmerm.github.io/webStuff/maze.html

My favorite way is to use Kruskal's algorithm, but when randomly choosing and edge to remove, weight the choice based on the types of edges it's connected to.

By varying the weights for different edge types, you can generate mazes with lots of distinct characteristics or "personalities". See my example here:

https://mtimmerm.github.io/webStuff/maze.html

羁客 2024-07-12 21:47:43

奇怪的是,通过稍微改变“规范”规则并从随机配置开始,康威的生命游戏 似乎生成了非常漂亮的迷宫!

(我不记得确切的规则,但这是一个非常简单的修改,往往会“致密”细胞群......)

Strangely enough, by slightly changing the 'canonical' rules and starting from a random configuration, Conway's Game of Life seems to generate pretty nice mazes!

(I don't remember the exact rule, but it's a very simple modification that tends to 'densify' the population of cells...)

如痴如狂 2024-07-12 21:47:43

递归回溯是最容易实现的算法。

这是一个 Java 实现:

这里 Cell 是一个表示 2D 网格中单元格的类,cellsCell 对象的 2D 数组。 Cell 有布尔变量 topbottomleftright 来指示是否单元格的这些侧面都有墙,一个布尔变量visited来检查我们是否已经遍历它,两个整数变量rowcol来指示它的位置在网格中。

Cell current = cells[0][0] , next;
    current.visited=true;
    do{
        next = getNeighbour(current);
        if(next!=null){
            removeWall(current , next);
            st.push(current);
            current = next;
            current.visited = true;
        }
        else {
            current = st.pop();
        }
    }
    while (!st.empty());


    private Cell getNeighbour(Cell cell){
    ArrayList<Cell> ara = new ArrayList<>();
    if(cell.col>0 && !cells[cell.col-1][cell.row].visited)
         ara.add(cells[cell.col-1][cell.row]);

    if(cell.row>0 && !cells[cell.col][cell.row-1].visited)
         ara.add(cells[cell.col][cell.row-1]);

    if(cell.col<col-1 && !cells[cell.col+1][cell.row].visited)
         ara.add(cells[cell.col+1][cell.row]);
    if(cell.row<row-1 && !cells[cell.col][cell.row+1].visited)
         ara.add(cells[cell.col][cell.row+1]); 


    if(ara.size()>0){
        return ara.get(new Random().nextInt(ara.size()));
    }else{
        return null;
    }
}
private void removeWall(Cell curr , Cell nxt){
    if((curr.col == nxt.col) && (curr.row == nxt.row+1)){/// top
        curr.top=nxt.botttom=false;
    }
    if(curr.col==nxt.col && curr.row == nxt.row-1){///bottom
        curr.botttom = nxt.top = false;
    }
    if(curr.col==nxt.col-1 && curr.row==nxt.row ){///right
        curr.right = nxt.left = false;
    }
    if(curr.col == nxt.col+1 && curr.row == nxt.row){///left
        curr.left = nxt.right = false;
    }
}

Recursive Backtracking is the easiest algorithm to implement.

Here's a Java implementation:

Here Cell is a class representing a cell in a 2D grid and cells is a 2D array of Cell objects. Cell has boolean variables top, bottom, left and right to indicate whether a cell has walls on these sides, a boolean variable visited to check whether we have traversed it and two integer variables row and col to indicate its position in the grid.

Cell current = cells[0][0] , next;
    current.visited=true;
    do{
        next = getNeighbour(current);
        if(next!=null){
            removeWall(current , next);
            st.push(current);
            current = next;
            current.visited = true;
        }
        else {
            current = st.pop();
        }
    }
    while (!st.empty());


    private Cell getNeighbour(Cell cell){
    ArrayList<Cell> ara = new ArrayList<>();
    if(cell.col>0 && !cells[cell.col-1][cell.row].visited)
         ara.add(cells[cell.col-1][cell.row]);

    if(cell.row>0 && !cells[cell.col][cell.row-1].visited)
         ara.add(cells[cell.col][cell.row-1]);

    if(cell.col<col-1 && !cells[cell.col+1][cell.row].visited)
         ara.add(cells[cell.col+1][cell.row]);
    if(cell.row<row-1 && !cells[cell.col][cell.row+1].visited)
         ara.add(cells[cell.col][cell.row+1]); 


    if(ara.size()>0){
        return ara.get(new Random().nextInt(ara.size()));
    }else{
        return null;
    }
}
private void removeWall(Cell curr , Cell nxt){
    if((curr.col == nxt.col) && (curr.row == nxt.row+1)){/// top
        curr.top=nxt.botttom=false;
    }
    if(curr.col==nxt.col && curr.row == nxt.row-1){///bottom
        curr.botttom = nxt.top = false;
    }
    if(curr.col==nxt.col-1 && curr.row==nxt.row ){///right
        curr.right = nxt.left = false;
    }
    if(curr.col == nxt.col+1 && curr.row == nxt.row){///left
        curr.left = nxt.right = false;
    }
}
殊姿 2024-07-12 21:47:43

事实证明,有 11 种经典算法可以生成“完美”迷宫。 如果迷宫只有一种解决方案,那么它就是完美的。 以下是每个算法的一些链接,按照我的偏好大致顺序排列。

  1. 克鲁斯卡尔的
  2. Prim 的
  3. 递归回溯器
  4. Aldous-Broder
  5. 成长树
  6. 狩猎和杀戮
  7. 威尔逊的
  8. 埃勒的
  9. 递归除法(可预测)
  10. 响尾蛇 (可预测)
  11. 二叉树(有缺陷)

有关更多信息,请查看 mazelib GitHub,一个实现所有标准迷宫生成/求解算法的 Python 库。

It turns out there are 11 classic algorithms to generate "perfect" mazes. A maze is perfect if it has one, and only one, solution. Here are some links to each algorithm, in rough order of my preference.

  1. Kruskal's
  2. Prim's
  3. Recursive Backtracker
  4. Aldous-Broder
  5. Growing Tree
  6. Hunt-and-Kill
  7. Wilson's
  8. Eller's
  9. Recursive Division (Predictable)
  10. Sidewinder (Predictable)
  11. Binary Tree (Flawed)

For more info, check out mazelib on GitHub, a Python library implementing all the standard maze generating/solving algorithms.

听你说爱我 2024-07-12 21:47:43

生成迷宫的方法之一是 Prim 算法的随机版本。

从充满墙壁的网格开始。
选择一个单元格,将其标记为迷宫的一部分。 将单元格的墙壁添加到墙壁列表中。
当列表中有墙时:

从列表中随机选择一堵墙。 如果对面的单元格尚未进入迷宫:

(i) 将墙壁设为通道,并将对面的单元格标记为迷宫的一部分。

(ii) 将单元格的相邻墙壁添加到墙壁列表中。

如果对面的单元格已经在迷宫中,则从列表中删除墙。

One of the methods to generate a maze is the randomized version of Prim's algorithm.

Start with a grid full of walls.
Pick a cell, mark it as part of the maze. Add the walls of the cell to the wall list.
While there are walls in the list:

Pick a random wall from the list. If the cell on the opposite side isn't in the maze yet:

(i) Make the wall a passage and mark the cell on the opposite side as part of the maze.

(ii) Add the neighboring walls of the cell to the wall list.

If the cell on the opposite side already was in the maze, remove the wall from the list.

不喜欢何必死缠烂打 2024-07-12 21:47:43

这是用伪代码编写的 DFS 算法:

创建一个 CellStack (LIFO) 来保存单元位置列表
设置 TotalCells = 网格中的单元格数量
随机选择一个单元格并将其命名为 CurrentCell
设置 VisitedCells = 1

当 VisitedCells < 时 细胞总数
找到 CurrentCell 的所有邻居且所有墙壁都完好无损
如果找到一个或多个
随机选择一个
推倒它和 CurrentCell 之间的墙
将 CurrentCell 位置推送到 CellStack
使新单元格成为 CurrentCell
将 1 添加到 VisitedCells
别的
从 CellStack 中弹出最新的单元条目
使其成为当前单元格
万一
结束时

Here's the DFS algorithm written as pseudocode:

create a CellStack (LIFO) to hold a list of cell locations
set TotalCells = number of cells in grid
choose a cell at random and call it CurrentCell
set VisitedCells = 1

while VisitedCells < TotalCells
find all neighbors of CurrentCell with all walls intact
if one or more found
choose one at random
knock down the wall between it and CurrentCell
push CurrentCell location on the CellStack
make the new cell CurrentCell
add 1 to VisitedCells
else
pop the most recent cell entry off the CellStack
make it CurrentCell
endIf
endWhile

肥爪爪 2024-07-12 21:47:43

我更喜欢递归除法算法的一个版本。 此处详细描述。

< strong>我将快速概述:
原始递归除法算法的工作原理如下。 首先,从迷宫的空白区域开始。 添加一堵直墙将房间一分为二,并在该墙上的某处打一个洞。 然后,在两个新室中的每一个上递归地重复此过程,直到达到所需的通道尺寸。 这很简单并且效果很好,但是存在明显的瓶颈,使得迷宫很容易解决。

该变体通过绘制随机的“弯曲”墙而不是直墙来解决这个问题,从而使瓶颈不那么明显。

I prefer a version of the Recursive Division algorithm. It is described in detail here.

I will give a quick overview:
The original recursive division algorithm works as follows. First, start with an empty area for the maze. Add one straight wall to divide the chamber in two, and put one hole in that wall somewhere. Then, recursively repeat this process on each of the two new chambers until the desired passage size is reached. This is simple and works well, but there are obvious bottlenecks which make the maze easy to solve.

The variant solves this problem by drawing randomized, "curved" walls rather than straight ones, making the bottlenecks less obvious.

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