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function Depth-Limited-Search-Backward(u, Δ, B, F) is prepend u to B if Δ = 0 then if u in F then return u (Reached the marked node, use it as a relay node) remove the head node of B return null foreach parent of u do μ ← Depth-Limited-Search-Backward(parent, Δ − 1, B, F) if μ null then return μ remove the head node of B return null
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.
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 only one of the cells that the wall divides is visited, then: Make the wall a passage and mark the unvisited cell as part of the maze. Add the neighboring walls of the cell to the wall list.
A difference list f is a single-argument function append L, which when given a linked list X as argument, returns a linked list containing L prepended to X. Concatenation of difference lists is implemented as function composition. The contents may be retrieved using f []. [1]
The function strongconnect performs a single depth-first search of the graph, finding all successors from the node v, and reporting all strongly connected components of that subgraph. When each node finishes recursing, if its lowlink is still set to its index, then it is the root node of a strongly connected component, formed by all of the ...
In computer science, the range searching problem consists of processing a set S of objects, in order to determine which objects from S intersect with a query object, called the range. For example, if S is a set of points corresponding to the coordinates of several cities, find the subset of cities within a given range of latitudes and longitudes .
In the analysis of algorithms, the input to breadth-first search is assumed to be a finite graph, represented as an adjacency list, adjacency matrix, or similar representation. However, in the application of graph traversal methods in artificial intelligence the input may be an implicit representation of an infinite graph. In this context, a ...
In computer science, cycle detection or cycle finding is the algorithmic problem of finding a cycle in a sequence of iterated function values.. For any function f that maps a finite set S to itself, and any initial value x 0 in S, the sequence of iterated function values