Alpha-Beta Pruning — AI Technical Interview Questions & Answers

Alpha-Beta Pruning

Alpha-Beta Pruning

  • Alpha-beta pruning skips branches that cannot change the minimax decision. Alpha is the best max can already force. Beta is the best min can already force. If a node becomes worse than that window, stop expanding it. Same answer as minimax, fewer nodes.
  • Order matters: good move ordering prunes more. Viva: “same result as minimax, less work”. Don’t say it makes a different (smarter) strategy.
  • Alpha-Beta Pruning — output: three lines. Not a different strategy — less work.

Technical Interview Tip: Same result as minimax + why order helps.

Code Examples for Alpha-Beta Pruning

Example

# Alpha-beta idea
print("minimax value stays the same")
print("alpha/beta skip branches that cannot change the decision")
print("better move order → more prune")

Alpha-Beta Pruning — output: three lines. Not a different strategy — less work.

How to Explain Alpha-Beta Pruning to an Interviewer

Explain Alpha-Beta Pruning as if you are teaching a junior — definition, then one example.

Prune useless minimax branches. Same value, fewer nodes.

What does the example print, and what does that prove?

Alpha-Beta Pruning — output: three lines

What mistake do freshers make with Alpha-Beta Pruning?

alpha / beta window.