What is A/B testing in AI campaigns, and how do bandit algorithms differ in allocation strategy?

• A. A/B tests compare fixed variants; bandits allocate more traffic to better-performing variants in real time, reducing learning time and exposure to underperformers.
• B. A/B tests continuously rotate all variants evenly; bandits always assign equal traffic to all variants.
• C. A/B tests optimize pricing directly; bandits adjust budgets accordingly.
• D. A/B tests use machine learning to predict outcomes after the campaign ends.

Answer: (A)