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What is the meaning of 'breadth' in breadth first search?
Planned maintenance scheduled April 23, 2019 at 00:00UTC (8:00pm US/Eastern)
Announcing the arrival of Valued Associate #679: Cesar Manara
Unicorn Meta Zoo #1: Why another podcast?Unique path in a directed graphWhen would best first search be worse than breadth first search?Dijkstra algorithm vs breadth first search for shortest path in graphHow do we generate a depth-first forest from the Depth First Search?Time complexity of Depth First SearchBreadth First Search actually require specifically Queue instead of any other type of Collection?Understanding connection between minimum spanning tree, shortest path, breadth first and depth first traversalProof that G is a Tree After DFS and BFS form the same tree TDijkstra’s versus Lowest-cost-first (best first), resolving some contradictions regarding complexity analysisIs Breadth First Search Space Complexity on a Grid different?
$begingroup$
I was learning about breadth first search and a question came in my mind that why BFS is called so. In the book Introduction to Algorithms by CLRS, I read the following reason for this:
Breadth-first search is so named because it expands the frontier
between discovered and undiscovered vertices uniformly across the
breadth of the frontier.
However, I'm not able to understand the meaning of this statement. I'm confused about this word "frontier" and breadth of that frontier.
So, can someone please answer this question in a way which is easy to understand for a beginner like me?
graphs graph-theory shortest-path graph-traversal
$endgroup$
add a comment |
$begingroup$
I was learning about breadth first search and a question came in my mind that why BFS is called so. In the book Introduction to Algorithms by CLRS, I read the following reason for this:
Breadth-first search is so named because it expands the frontier
between discovered and undiscovered vertices uniformly across the
breadth of the frontier.
However, I'm not able to understand the meaning of this statement. I'm confused about this word "frontier" and breadth of that frontier.
So, can someone please answer this question in a way which is easy to understand for a beginner like me?
graphs graph-theory shortest-path graph-traversal
$endgroup$
add a comment |
$begingroup$
I was learning about breadth first search and a question came in my mind that why BFS is called so. In the book Introduction to Algorithms by CLRS, I read the following reason for this:
Breadth-first search is so named because it expands the frontier
between discovered and undiscovered vertices uniformly across the
breadth of the frontier.
However, I'm not able to understand the meaning of this statement. I'm confused about this word "frontier" and breadth of that frontier.
So, can someone please answer this question in a way which is easy to understand for a beginner like me?
graphs graph-theory shortest-path graph-traversal
$endgroup$
I was learning about breadth first search and a question came in my mind that why BFS is called so. In the book Introduction to Algorithms by CLRS, I read the following reason for this:
Breadth-first search is so named because it expands the frontier
between discovered and undiscovered vertices uniformly across the
breadth of the frontier.
However, I'm not able to understand the meaning of this statement. I'm confused about this word "frontier" and breadth of that frontier.
So, can someone please answer this question in a way which is easy to understand for a beginner like me?
graphs graph-theory shortest-path graph-traversal
graphs graph-theory shortest-path graph-traversal
edited 3 hours ago
DG4
asked 4 hours ago
DG4DG4
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$begingroup$
Consider the data structure used to represent the search. In a BFS, you use a queue. If you come across an unseen node, you add it to the queue.
The “frontier” is the set of all nodes in the search data structure. The queue will will iterate through all nodes on the frontier sequentially, thus iterating across the breadth of the frontier. DFS will always pop the most recently discovered state off of the stack, thus always iterating over the deepest part of the frontier.
Consider the image below. Notice how the DFS goes straight to the deepest parts of the tree whereas BFS iterates over the breadth of each level.
Image here
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$begingroup$
Consider the data structure used to represent the search. In a BFS, you use a queue. If you come across an unseen node, you add it to the queue.
The “frontier” is the set of all nodes in the search data structure. The queue will will iterate through all nodes on the frontier sequentially, thus iterating across the breadth of the frontier. DFS will always pop the most recently discovered state off of the stack, thus always iterating over the deepest part of the frontier.
Consider the image below. Notice how the DFS goes straight to the deepest parts of the tree whereas BFS iterates over the breadth of each level.
Image here
New contributor
$endgroup$
add a comment |
$begingroup$
Consider the data structure used to represent the search. In a BFS, you use a queue. If you come across an unseen node, you add it to the queue.
The “frontier” is the set of all nodes in the search data structure. The queue will will iterate through all nodes on the frontier sequentially, thus iterating across the breadth of the frontier. DFS will always pop the most recently discovered state off of the stack, thus always iterating over the deepest part of the frontier.
Consider the image below. Notice how the DFS goes straight to the deepest parts of the tree whereas BFS iterates over the breadth of each level.
Image here
New contributor
$endgroup$
add a comment |
$begingroup$
Consider the data structure used to represent the search. In a BFS, you use a queue. If you come across an unseen node, you add it to the queue.
The “frontier” is the set of all nodes in the search data structure. The queue will will iterate through all nodes on the frontier sequentially, thus iterating across the breadth of the frontier. DFS will always pop the most recently discovered state off of the stack, thus always iterating over the deepest part of the frontier.
Consider the image below. Notice how the DFS goes straight to the deepest parts of the tree whereas BFS iterates over the breadth of each level.
Image here
New contributor
$endgroup$
Consider the data structure used to represent the search. In a BFS, you use a queue. If you come across an unseen node, you add it to the queue.
The “frontier” is the set of all nodes in the search data structure. The queue will will iterate through all nodes on the frontier sequentially, thus iterating across the breadth of the frontier. DFS will always pop the most recently discovered state off of the stack, thus always iterating over the deepest part of the frontier.
Consider the image below. Notice how the DFS goes straight to the deepest parts of the tree whereas BFS iterates over the breadth of each level.
Image here
New contributor
New contributor
answered 2 hours ago
Bryce KilleBryce Kille
665
665
New contributor
New contributor
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