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Which search method takes less memory?

This is a question our experts keep getting from time to time. Now, we have got a complete detailed explanation and answer for everyone, who is interested!

Which search method takes less memory? Explanation: Depth-First Search takes less memory since only the nodes on the current path are stored, but in Breadth First Search, all of the tree that has generated must be stored. 15.

What complete optimal search algorithm uses the least memory?

  • DFS requires very less memory as it only needs to store a stack of the nodes on the path from root node to the current node.
  • It takes less time to reach to the goal node than BFS algorithm (if it traverses in the right path).

Which is the best way to go for game playing problem *?

Explanation: we use a heuristic approach, as it will find out brute force computation, looking at hundreds of thousands of positions. e.g chess competition between human and ai based computer.

Which is the most straightforward approach for planning algorithm?

Which is the most straightforward approach for planning algorithm? Explanation: The straightforward approach for planning algorithm is state space search because it takes into account of everything for finding a solution.

Which search is complete and optimal when HN is consistent?

Which search is complete and optimal when h(n) is consistent? Explanation: None.

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34 related questions found

Will A * always find the lowest cost path?

If the heuristic function is admissible, meaning that it never overestimates the actual cost to get to the goal, A* is guaranteed to return a least-cost path from start to goal.

Why is A * better than best-first search?

Best First Search Example

So in summary, both Greedy BFS and A* are Best first searches but Greedy BFS is neither complete, nor optimal whereas A* is both complete and optimal. However, A* uses more memory than Greedy BFS, but it guarantees that the path found is optimal.

What is used in backward chaining algorithm?

Backward-chaining is based on modus ponens inference rule. In backward chaining, the goal is broken into sub-goal or sub-goals to prove the facts true. It is called a goal-driven approach, as a list of goals decides which rules are selected and used.

What is the complexity of Minimax algorithm?

The time complexity of minimax is O(b^m) and the space complexity is O(bm), where b is the number of legal moves at each point and m is the maximum depth of the tree.

How many terms are required for building a Bayes model?

1. How many terms are required for building a bayes model? Explanation: The three required terms are a conditional probability and two unconditional probability.

What are main goals of AI?

The basic objective of AI (also called heuristic programming, machine intelligence, or the simulation of cognitive behavior) is to enable computers to perform such intellectual tasks as decision making, problem solving, perception, understanding human communication (in any language, and translate among them), and the …

Which is used to improve the agents performance?

Which is used to improve the agents performance? Explanation: An agent can improve its performance by storing its previous actions. 8.

Who is called father of AI?

John McCarthy, an American computer scientist pioneer and inventor, was known as the father of Artificial Intelligence (AI) after playing a seminal role in defining the field devoted to the development of intelligent machines.

Why is A * optimal?

A* search is optimal if the heuristic is admissible. Admissible makes that whichever node you expand, it makes sure that the current estimate is always smaller than the optimal, so path about to expand maintains a chance to find the optimal path.

WHAT IS A * algorithm in AI?

A * algorithm is a searching algorithm that searches for the shortest path between the initial and the final state. It is used in various applications, such as maps. In maps the A* algorithm is used to calculate the shortest distance between the source (initial state) and the destination (final state).

What is advantage of A * graph search over A * tree search?

The advantage of graph search obviously is that, if we finish the search of a node, we will never search it again. On the other hand, the tree search can visit the same node multiple times. The disadvantage of graph search is that it uses more memory (which we may or may not have) than tree search.

What is the complexity of maximum algorithm?

Return max and min. Time Complexity is O(n) and Space Complexity is O(1). For each pair, there are a total of three comparisons, first among the elements of the pair and the other two with min and max.

Which algorithm is used in the game tree to make decisions of Win Loss?

10) Which algorithm is used in the Game tree to make decisions of Win/Lose? Explanation: A game tree is a directed graph whose nodes represent the positions in Game and edges represent the moves. To make any decision, the game tree uses the Min/Max algorithm.

What is the complexity of DFS?

The time complexity of DFS if the entire tree is traversed is O(V) where V is the number of nodes. If the graph is represented as adjacency list: Here, each node maintains a list of all its adjacent edges.

What is an example of backward chaining?

Use backward chaining (i.e., breaking a skill down into smaller steps, then teaching and reinforcing the last step in the sequence first, then the second to the last step, and so on). For example, have the child wash his/her hands in the sink near the toilet.

How do you do backward chaining?

So what is backward chaining? You start by breaking the task down into small steps. You teach your child the last step first, working backwards from the goal. You complete all the steps except the last one.

What is backward chaining inference method?

Backward chaining (or backward reasoning) is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers, inference engines, proof assistants, and other artificial intelligence applications. … Both rules are based on the modus ponens inference rule.

What is difference between A * and AO * algorithm?

An A* algorithm represents an OR graph algorithm that is used to find a single solution (either this or that). An AO* algorithm represents an AND-OR graph algorithm that is used to find more than one solution by ANDing more than one branch.

HOW DOES A * search extend best-first search?

A* is an informed search algorithm, or a best-first search, meaning that it is formulated in terms of weighted graphs: starting from a specific starting node of a graph, it aims to find a path to the given goal node having the smallest cost (least distance travelled, shortest time, etc.).

Why is a * Search complete?

A* is complete, optimal, and it has a time and space complexity of O(bm). So, in general, A* uses more memory than greedy BFS. A* becomes impractical when the search space is huge.