Living Broadly

What is the BFS algorithm? 

 

The breadth-first search (BFS) algorithm is used to search a tree or graph data structure for a node that meets a set of criteria. It starts at the tree’s root or graph and searches/visits all nodes at the current depth level before moving on to the nodes at the next depth level. Breadth-first search can be used to solve many problems in graph theory. It’s generally used to find the shortest path to a node from some given node when the edges have no or the same weights on them.

 

What if there are infinite paths around us, and wisdom monstrously asks demandingly… What is the wise path that is necessary to take now and in every moment? If you do not take the wise path you will harm yourself in the future. How to know what path to choose?  Wouldn’t it be wiser to visit broadly first, before choosing? accumulating experience and wisdom before answering? To Unearth the truth and the essential. 

Implementation of BFS traversal

To implement BFS traversal, use the method outlined below.

  • Declare a queue and add the initial vertex to it.
  • Mark the initial vertex of the visited array as visited.
  • Follow the steps below until the line is empty:
  • Remove the initial vertex from the list.
  • Mark visited this vertex.
  • Insert into the queue all unvisited neighbors of the vertex.

No one can build you the bridge on which you, and only you, must cross the river of life,” Nietzsche

Couldn’t it be developing wisdom and philosophy a layer in the graph of life? What is the first subjectively wise layer? What is the graph? and What are edges and nodes? what is the first thought or action? What are the source node and layer?

Search strategies solve all AI problems. AI rational agents employ these search strategies or algorithms to solve the issues and get the best solution.

 

visited = [] # List for visited nodes.
queue = [] #Initialize a queue

def bfs(visited, graph, node): #function for BFS
  visited.append(node)
  queue.append(node)

  while queue: # Creating loop to visit each node
    m = queue.pop(0) 
    print (m, end = " ") 

    for neighbour in graph[m]:
      if neighbour not in visited:
        visited.append(neighbour)
        queue.append(neighbour)

Such “free spirits” do not really exist and never did exist. But I stood in need of them, as I have pointed out, in order that some good might be mixed with my evils…. with whom one may talk and laugh when one is disposed to talk and laugh, and whom one may send to the devil when they grow wearisome… [And] I see them already coming, slowly, slowly. May it not be that I am doing a little something to expedite their coming when I describe in advance the influences under which I see them evolving and the ways along which they travel?- Nietzsche

 

The search strategy is complete if it is guaranteed to locate a goal state if it exists. The breadth-first search is exhaustive, whereas the depth-first search is incomplete. When applied to infinite graphs represented implicitly, the breadth-first search will ultimately locate the goal state, whereas the depth-first search may become lost in portions of the graph that lack a goal and never return. 

 

I undertook something that not everyone may undertake: I descended into the depths, I bored into the foundations…Whoever looks into himself as into an enormous world space and carries galaxies within him, he knows how irregular all galaxies are: they lead right into the chaos and labyrinth of existence… Nietzsche

 

Applications

We can utilize breadth-first search to tackle numerous problems in graph theory, including:

  • Cheney’s algorithm mimics garbage collection.
  • Finding the shortest edge-length path between two nodes, u and v.
  • Cuthill–McKee mesh identification
  • The Ford–Fulkerson method for determining the maximum flow in a flow network
  • Serialization/Deserialization of a binary tree enables efficient tree reconstruction.
  • The failure function of the Aho-Corasick pattern matcher is constructed.
  • Graph bipartite ness evaluation
  • We can use similar techniques to compute the transitive closure of a graph.

 

 

A soul in which the type of “free spirit” can attain maturity and completeness had its decisive and deciding event in the form of a great emancipation or unbinding, and that prior to that event it seemed only the more firmly and forever chained to its place and pillar… The great liberation comes suddenly to such prisoners, like an earthquake: the young soul is all at once shaken, torn apart, cast forth — it comprehends not itself what is taking place. An involuntary onward impulse rules them with the mastery of command; a will, a wish are developed to go forward… a mutinous, willful, volcanic-like longing for a far away journey… 

A Human of such destiny … basks in a special fine sun of his own, with a feeling of birdlike freedom, birdlike visual power, birdlike irrepressibleness, a something extraneous (Drittes) in which curiosity and delicate disdain have united. A “free spirit” — this refreshing term is grateful in any mood, it almost sets one aglow. One lives — no longer in the bonds of love and hate, without a yes or no, here or there indifferently, best pleased to evade, to avoid, to beat about, neither advancing nor retreating… – Nietzche 

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