방법 비교

	적응형 A/B 테스트	AB 설계
분야	실험설계	실험설계
계열	Process / pipeline	Process / pipeline
기원 연도	1952 (Robbins); applied to A/B testing from ~2010s onward	1960s
창시자	Herbert Robbins (bandit framework); Thompson Sampling formalized by William R. Thompson	Murray Sidman; Baer, Wolf & Risley
유형	Adaptive experimental design	Single-subject experimental design
원전	Russo, D., Van Roy, B., Kazerouni, A., Osband, I., & Wen, Z. (2018). A Tutorial on Thompson Sampling. Foundations and Trends in Machine Learning, 11(1), 1–96.	Sidman, M. (1960). Tactics of Scientific Research: Evaluating Experimental Data in Psychology. Basic Books.
별칭	adaptive AB test, bandit A/B test, multi-armed bandit testing, online adaptive experiment	baseline-intervention design, AB single-case design, AB phase design
관련	6	4
요약	An Adaptive A/B test is an experimental design that dynamically reallocates traffic or participants toward better-performing variants during the experiment itself, rather than holding allocations fixed until the end. Drawing on multi-armed bandit algorithms such as Thompson Sampling or Upper Confidence Bound (UCB), it balances the exploration of uncertain variants with the exploitation of those already showing superior performance, typically yielding higher aggregate outcomes while still producing valid inferential conclusions.	The AB design is the simplest single-subject experimental design, consisting of two sequential phases: a baseline phase (A) in which the target behavior is observed under natural conditions without intervention, followed by an intervention phase (B) in which the treatment or manipulation is introduced. Changes in the behavior's level, trend, or variability between phases are used to infer the effect of the intervention on the individual participant.