방법 비교

	적응형 A/B 테스트	Randomized Controlled Trial (RCT)
분야	실험설계	실험설계
계열	Process / pipeline	Hypothesis test
기원 연도	1952 (Robbins); applied to A/B testing from ~2010s onward	1948
창시자	Herbert Robbins (bandit framework); Thompson Sampling formalized by William R. Thompson	James Lind (early precursor, 1747); modern formulation: Austin Bradford Hill & Medical Research Council (1948)
유형	Adaptive experimental design	Interventional comparative study
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.	Schulz, K.F., Altman, D.G., Moher, D., for the CONSORT Group (2010). CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomised Trials. BMJ, 340, c332.
별칭	adaptive AB test, bandit A/B test, multi-armed bandit testing, online adaptive experiment	RCT, randomised controlled trial, clinical trial, Randomize Kontrollü Çalışma (RCT) Tasarımı
관련	6	7
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.	A randomized controlled trial (RCT) is the gold standard experimental design in clinical and health research, in which participants are randomly allocated to a treatment group or a control group so that the effect of an intervention can be measured with the highest possible degree of internal validity. The modern parallel-group RCT was formalized by Austin Bradford Hill and the Medical Research Council in their landmark streptomycin trial of 1948, and its reporting is governed today by the CONSORT 2010 guidelines (Schulz et al., 2010).