CS50-AI-1

Question 1

Node; Data structure in search algorithms representing a state

Answer 1

its parent

Question 2

How do depth-first and breadth-first search differ in their approach to exploring the state space

Answer 2

and in what scenarios might each be more efficient?; Depth-first search (DFS) explores as deep as possible along each branch before backtracking

Question 3

Compare greedy best-first search and A search in terms of their use of heuristic functions and overall efficiency in finding solutions.; * Greedy best-first search uses a heuristic to prioritize nodes closest to the goal

Answer 3

focusing on the estimated distance to the goal. A* search combines the cost to reach the current node and a heuristic estimate to the goal

Question 4

In adversarial search

Answer 4

how does the Minimax algorithm’s strategy differ when facing a maximizing player versus a minimizing player?; In adversarial search

Question 5

Explain the role of alpha-beta pruning in optimizing the Minimax algorithm

Answer 5

and how it affects the algorithm’s performance.; Alpha-beta pruning enhances the Minimax algorithm by eliminating branches in the search tree that do not influence the final decision

Question 6

How does the concept of path cost influence the choice of actions in a search problem?; In search problems

Answer 6

path cost influences the choice of actions by prioritizing paths with lower costs

Question 7

Discuss the trade-offs between depth-limited Minimax and standard Minimax in terms of computational efficiency and solution optimality.; Depth-limited Minimax limits the depth of the search tree

Answer 7

improving computational efficiency by reducing the search space. However

Question 8

Describe how the frontier functions differently in depth-first search compared to breadth-first search.; In depth-first search

Answer 8

the frontier functions as a stack where the most recently added node is explored next