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Graph traversal is a subroutine in most graph algorithms. The goal of a graph traversal algorithm is to visit (and / or process) every node of a graph. Graph traversal algorithms, like breadth-first search and depth-first search, are analyzed using the von Neumann model, which assumes uniform memory access cost. This view neglects the fact ...
A sampling-based planner works by searching the graph. In the case of path planning, the graph contains the spatial nodes which can be observed by the robot. The wavefront expansion increases the performance of the search by analyzing only nodes near the robot. The decision is made on a geometrical level which is equal to breadth-first search. [5]
[3] Breadth-first search can be generalized to both undirected graphs and directed graphs with a given start node (sometimes referred to as a 'search key'). [4] In state space search in artificial intelligence, repeated searches of vertices are often allowed, while in theoretical analysis of algorithms based on breadth-first search, precautions ...
Parallel breadth-first search; Parallel single-source shortest path algorithm; Path-based strong component algorithm; Pre-topological order; Prim's algorithm; Proof-number search; Push–relabel maximum flow algorithm
The breadth-first-search algorithm is a way to explore the vertices of a graph layer by layer. It is a basic algorithm in graph theory which can be used as a part of other graph algorithms. It is a basic algorithm in graph theory which can be used as a part of other graph algorithms.
A universal traversal sequence is a sequence of instructions comprising a graph traversal for any regular graph with a set number of vertices and for any starting vertex. A probabilistic proof was used by Aleliunas et al. to show that there exists a universal traversal sequence with number of instructions proportional to O ( n 5 ) for any ...
The d-ary heap consists of an array of n items, each of which has a priority associated with it. These items may be viewed as the nodes in a complete d-ary tree, listed in breadth first traversal order: the item at position 0 of the array (using zero-based numbering) forms the root of the tree, the items at positions 1 through d are its children, the next d 2 items are its grandchildren, etc.
Gremlin's automata and functional language foundation enable Gremlin to naturally support: imperative and declarative querying; host language agnosticism; user-defined domain specific languages; an extensible compiler/optimizer, single- and multi-machine execution models; hybrid depth- and breadth-first evaluation with Turing completeness.