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## Does minimax use depth-first search?

Minimax is a depth-first, depth-limited search procedure, and is the prevaling strategy for searching game trees. Minimax searches down to a certain depth, and treats the nodes at that depth as if they were terminal nodes, invoking a heuristic function (called a static evaluation function) to determine their values.

**Why is depth-first search preferred over a search?**

Depth First Search is commonly used when you need to search the entire tree. It’s easier to implement (using recursion) than BFS, and requires less state: While BFS requires you store the entire ‘frontier’, DFS only requires you store the list of parent nodes of the current element.

**Is the MIN MAX a depth first or breadth first search algorithm?**

Minimax is better implemented as a depth-first search, which requires only a linear amount of memory in relation to tree depth. The data structure used for this search is a stack, either through recursive function calls or a direct stack based implementation without the function call overhead.

### Why does the minimax algorithm is termed as minimax?

In zero-sum games The name minimax arises because each player minimizes the maximum payoff possible for the other—since the game is zero-sum, they also minimize their own maximum loss (i.e. maximize their minimum payoff). See also example of a game without a value.

**Is minimax DFS or BFS?**

Minimax uses DFS to evaluate nodes.

**What is depth first search in graph?**

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.

## When would DFS be a better choice than a * Search?

If you know a solution is not far from the root of the tree, a breadth first search (BFS) might be better. If the tree is very deep and solutions are rare, depth first search (DFS) might take an extremely long time, but BFS could be faster.

**Is Minimax DFS or BFS?**

**What is BFS and DFS explain with example?**

BFS(Breadth First Search) uses Queue data structure for finding the shortest path. DFS(Depth First Search) uses Stack data structure. BFS can be used to find single source shortest path in an unweighted graph, because in BFS, we reach a vertex with minimum number of edges from a source vertex.

### How does adversarial search for the minimax procedure work?

Hence adversarial Search for the minimax procedure works as follows: It aims to find the optimal strategy for MAX to win the game. It follows the approach of Depth-first search. In the game tree, optimal leaf node could appear at any depth of the tree.

**Which is the best definition of depth first search?**

Depth-first Search (DFS) is an algorithm for searching a graph or tree data structure. The algorithm starts at the root (top) node of a tree and goes as far as it can down a given branch (path), and then backtracks until it finds an unexplored path, and then explores it.

**Which is the most standard DFS search algorithm?**

This is the most standard DFS algorithm. Instead of visiting each node as it traverses down a tree, an in-order algorithm finds the leftmost node in the tree, visits that node, and subsequently visits the parent of that node. It then goes to the child on the right and finds the next leftmost node in the tree to visit.

## Which is better BFS or depth first search?

If it is known that an answer will likely be found far into a tree, DFS is a better option than BFS. BFS is good to use when the depth of the tree can vary or if a single answer is needed—for example, the shortest path in a tree. If the entire tree should be traversed, DFS is a better option.