Question:
What is the primary advantage of Alpha-Beta pruning over standard Minimax?
What is the primary advantage of Alpha-Beta pruning over standard Minimax?
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Alpha-Beta gives the same move as Minimax, so its benefit must be about speed, not a better result.
Updated On: Jul 2, 2026
- It always finds the optimal solution faster than any other algorithm
- It improves efficiency by pruning unnecessary branches in the search tree
- It guarantees a better result than Minimax
- It avoids the need for evaluating terminal nodes
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The Correct Option is B
Solution and Explanation
Step 1: Standard Minimax explores the whole game tree to choose a move. Alpha-Beta pruning is an optimization of Minimax.
Step 2: It keeps two bounds, alpha (best for the maximizer so far) and beta (best for the minimizer so far). When a branch cannot change the final decision, it is cut off and not explored.
Step 3: This cutting saves work, so the tree is searched faster. The final move chosen is the same as plain Minimax, so it does not give a better result. That rules out (C).
Step 4: It still evaluates terminal nodes where needed, so (D) is wrong. Option (A) overstates by claiming it beats any algorithm.
The real gain is efficiency from pruning useless branches.
Correct option: (B).
Step 2: It keeps two bounds, alpha (best for the maximizer so far) and beta (best for the minimizer so far). When a branch cannot change the final decision, it is cut off and not explored.
Step 3: This cutting saves work, so the tree is searched faster. The final move chosen is the same as plain Minimax, so it does not give a better result. That rules out (C).
Step 4: It still evaluates terminal nodes where needed, so (D) is wrong. Option (A) overstates by claiming it beats any algorithm.
The real gain is efficiency from pruning useless branches.
Correct option: (B).
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